hack/tools/scripts/llm-key-hunter/results/_cache/content/akitaonrails_llm-coding-benchmark.json

{"repo": "akitaonrails/llm-coding-benchmark", "files": {"results/glm_5_2/phase2-result.json": {"4ad84ee9510a59ddd101e621b23d6210358994b7": {"t": 1785674166.1253693, "n": 8003, "h": "b24fb4e5a69dfc48", "c": "{\n  \"assistant_output_excerpt\": \"Phase 2: end-to-end validation. Let me start by ensuring a clean state, then validate in order: local boot \\u2192 docker build \\u2192 docker compose.\\nRepo is clean. Let me first kill any lingering puma processes safely, then validate local boot.\\nThe `pkill -f puma` matches its own command string. Let me find and kill by PID instead:\\nShell is alive. Let me check running processes without killing:\\nNo lingering processes. Now step 1: validate local boot. I'll start the server in the background with proper PID management and a hard timeout to avoid hangs:\\nLocal boot passes (server up in 2s, health 200, SPA renders). Now let me validate a real chat message works end-to-end (RubyLLM \\u2192 OpenRouter \\u2192 Claude):\\nLet me inspect that response more carefully \\u2014 186KB is large. Let me check the log and response content:\\nCSRF protection is rejecting the bare curl POST (expected \\u2014 a real browser sends the token via Turbo). Let me simulate a real browser by extracting the CSRF token and cookie first:\\nLocal app fully validated \\u2014 real chat works: Claude Sonnet replied \\\"Hello there, friend!\\\" via OpenRouter/RubyLLM (200 OK in 1890ms). \\n\\nNow **step 2: docker build**. Let me verify prerequisites and run it:\\nDocker build succeeded \\u2014 image `rubyllm-chat:latest` built, assets precompiled inside the container. \\n\\nNow **step 3: docker compose up --build**. Let me source secrets and run it, then verify the container serves:\\nPort 80 is free and compose config resolves the key. (I'll avoid `compose config` going forward since it prints the key.) Now let me run `docker compose up --build`:\\nContainer started. Let me wait for the app to boot inside, then verify it serves correctly:\\nConnection failed (000). Let me check the container logs to diagnose:\\nThe app crashed on boot. Let me see the actual error at the top of the logs:\\nThe container crashes in production because `secret_key_base` is missing. I'll fix the entrypoint to auto-generate one at startup if not provided (no secret committed). Let me stop the container first:\\nNow fix the entrypoint to auto-generate `SECRET_KEY_BASE`:\\nNow rebuild and re-run docker compose:\\nContainer up. Let me wait for the app to boot inside and verify health + SPA:\\nContainer boots and serves. Now let me verify a real chat message works through the container (RubyLLM \\u2192 OpenRouter \\u2192 Claude):\\nFull chat works through the container \\u2014 Claude replied \\\"DUCK\\\" as requested. All three steps validated. Let me bring down the stack and run a final test sweep to confirm nothing regressed:\\nAll green. Final secret scan + verify entrypoint is executable:\\nPhase 2 validation complete. All steps pass end-to-end.\\n\\n## Validation results\\n\\n**1. Local app boots and runs** \\u2705\\n- Server boots in ~2s; `/up` health \\u2192 200; SPA renders (\\\"RubyLLM Chat\\\", empty state)\\n- **Real chat works**: posted \\\"Say hello in exactly 3 words\\\" \\u2192 Claude Sonnet replied \\\"Hello there, friend!\\\" via OpenRouter/RubyLLM (200 OK in 1890ms, with CSRF token + session cookie)\\n\\n**2. `docker build` finishes** \\u2705\\n- Multi-stage build succeeds; assets precompiled inside the container (esbuild + Tailwind); final image `rubyllm-chat:latest`\\n\\n**3. `docker compose up --build` runs** \\u2705\\n- Container serves on port 80; health \\u2192 200; SPA renders\\n- **Real chat through the container**: posted \\\"Reply with exactly: DUCK\\\" \\u2192 assistant bubble contains \\\"DUCK\\\"\\n\\n## Fix applied during validation\\n\\nThe production container crashed on boot with `Missing secret_key_base for 'production' environment`. Fixed `bin/docker-entrypoint` to auto-generate a random `SECRET_KEY_BASE` at startup when none is provided \\u2014 no secret is committed to any file (compose/Dockerfile/source).\\n\\n## Final CI state (all green)\\n\\n| Check | Result |\\n|-------|--------|\\n| Minitest | 26 runs, 59 assertions, 0 failures, **97.66% coverage** |\\n| RuboCop | no offenses |\\n| Brakeman | 0 security warnings |\\n| bundle-audit | no vulnerabilities |\\n| Secret scan | no real keys in repo |\",\n  \"command\": [\n    \"opencode\",\n    \"run\",\n    \"--agent\",\n    \"build\",\n    \"--format\",\n    \"json\",\n    \"--dir\",\n    \"/mnt/data/Projects/llm-coding-benchmark/results/glm_5_2/project\",\n    \"--session\",\n    \"ses_139708325ffeTky64xJTsqvSXw\",\n    \"Once finished coding and testing, you must make sure it runs, both locally, and that docker build also finishes successfully, and docker compose is able to run.\\n\\nDo not ask for confirmation. Do not stop with a plan. Fulfill the request and finish.\\n\\nThis is phase 2 of 2 and a continuation of the existing project in the current working directory. Do not regenerate the app. Do not create a second app. Validate and fix the current codebase in place.\\n\\nUse environment variables so RubyLLM actually works. Source ~/.config/zsh/secrets only to load the required environment, especially OPENROUTER_API_KEY. Do not print secret values, do not copy secret file contents into the repo, and do not commit secrets into files, logs, Dockerfiles, compose files, or README examples.\\n\\nValidate the project end-to-end in this order:\\n- run the local app in a way that proves it boots\\n- make any fixes needed so it boots cleanly\\n- make sure `docker build` finishes successfully\\n- make sure `docker compose up --build` is able to run\\n\\nIf one step passes, move to the next without asking for confirmation. If something fails, fix it and continue. Only stop when you have actually completed the validation work or you hit a hard blocker you cannot resolve from inside the workspace.\"\n  ],\n  \"continued_from_session\": \"ses_139708325ffeTky64xJTsqvSXw\",\n  \"elapsed_seconds\": 609.58,\n  \"ended_at\": \"2026-06-14T15:19:14+00:00\",\n  \"exit_code\": 0,\n  \"finish_reason\": \"stop\",\n  \"model\": {\n    \"id\": \"zai/glm-5.2\",\n    \"label\": \"GLM 5.2\",\n    \"provider\": \"zai\",\n    \"selection_reason\": \"Z.ai's newest flagship GLM (released 2026-06). Served on the coding plan endpoint at https://api.z.ai/api/coding/paas/v4 (live and key-verified 2026-06-14, though not yet in that endpoint's /models listing; not on OpenRouter yet). Like all GLM models it returns reasoning in reasoning_content with empty content by default \\u2014 the zai provider wiring already handles this for GLM 5.1. Tests whether 5.2 fixes 5.1's hallucinated chat.user/chat.assistant multi-turn DSL (the bug that put 5.1 in Tier C).\",\n    \"slug\": \"glm_5_2\"\n  },\n  \"no_progress_timeout_seconds\": 360,\n  \"opencode_session_id\": \"ses_139708325ffeTky64xJTsqvSXw\",\n  \"output_tokens_per_second\": 0.57,\n  \"paths\": {\n    \"opencode_config\": \"config/opencode.benchmark.json\",\n    \"project_dir\": \"results/glm_5_2/project\",\n    \"prompt\": \"results/glm_5_2/followup-prompt.txt\",\n    \"stderr\": \"results/glm_5_2/followup-opencode-stderr.log\",\n    \"stdout\": \"results/glm_5_2/followup-opencode-output.ndjson\"\n  },\n  \"phase\": \"phase2\",\n  \"preview_output_tokens_per_second\": 55.62,\n  \"preview_output_tokens_per_second_average\": 442.19,\n  \"project_summary\": {\n    \"file_count\": 811,\n    \"present\": {\n      \"app_dir\": true,\n      \"compose_yaml\": false,\n      \"compose_yml\": false,\n      \"docker_compose_yaml\": false,\n      \"docker_compose_yml\": true,\n      \"dockerfile\": true,\n      \"gemfile\": true,\n      \"javascript_dir\": true,\n      \"readme_lower\": false,\n      \"readme_md\": true,\n      \"routes\": true,\n      \"tests_dir\": true,\n      \"views_dir\": true\n    },\n    \"works_as_intended\": \"yes\",\n    \"works_note\": \"Rails app, tests, README, and container files detected.\"\n  },\n  \"prompt_sha256\": \"e2f60835f36832ba1242d6f23a02bd7958611c52f2db122a3df93f8727dab9b5\",\n  \"stall_reason\": null,\n  \"stalled\": false,\n  \"started_at\": \"2026-06-14T15:09:05+00:00\",\n  \"status\": \"completed\",\n  \"stderr_excerpt\": \"\",\n  \"timed_out\": false,\n  \"timeout_seconds\": 5400,\n  \"tokens\": {\n    \"cache\": {\n      \"read\": 91648,\n      \"write\": 0\n    },\n    \"input\": 435,\n    \"output\": 347,\n    \"reasoning\": 0,\n    \"total\": 92430\n  },\n  \"tokens_per_second\": 151.63\n}\n"}}, "results/glm_5_2/result.json": {"4ad84ee9510a59ddd101e621b23d6210358994b7": {"t": 1785674166.8207557, "n": 26211, "h": "39bcc8c197b33604", "c": "{\n  \"assistant_output_excerpt\": \"Phase 2: end-to-end validation. Let me start by ensuring a clean state, then validate in order: local boot \\u2192 docker build \\u2192 docker compose.\\nRepo is clean. Let me first kill any lingering puma processes safely, then validate local boot.\\nThe `pkill -f puma` matches its own command string. Let me find and kill by PID instead:\\nShell is alive. Let me check running processes without killing:\\nNo lingering processes. Now step 1: validate local boot. I'll start the server in the background with proper PID management and a hard timeout to avoid hangs:\\nLocal boot passes (server up in 2s, health 200, SPA renders). Now let me validate a real chat message works end-to-end (RubyLLM \\u2192 OpenRouter \\u2192 Claude):\\nLet me inspect that response more carefully \\u2014 186KB is large. Let me check the log and response content:\\nCSRF protection is rejecting the bare curl POST (expected \\u2014 a real browser sends the token via Turbo). Let me simulate a real browser by extracting the CSRF token and cookie first:\\nLocal app fully validated \\u2014 real chat works: Claude Sonnet replied \\\"Hello there, friend!\\\" via OpenRouter/RubyLLM (200 OK in 1890ms). \\n\\nNow **step 2: docker build**. Let me verify prerequisites and run it:\\nDocker build succeeded \\u2014 image `rubyllm-chat:latest` built, assets precompiled inside the container. \\n\\nNow **step 3: docker compose up --build**. Let me source secrets and run it, then verify the container serves:\\nPort 80 is free and compose config resolves the key. (I'll avoid `compose config` going forward since it prints the key.) Now let me run `docker compose up --build`:\\nContainer started. Let me wait for the app to boot inside, then verify it serves correctly:\\nConnection failed (000). Let me check the container logs to diagnose:\\nThe app crashed on boot. Let me see the actual error at the top of the logs:\\nThe container crashes in production because `secret_key_base` is missing. I'll fix the entrypoint to auto-generate one at startup if not provided (no secret committed). Let me stop the container first:\\nNow fix the entrypoint to auto-generate `SECRET_KEY_BASE`:\\nNow rebuild and re-run docker compose:\\nContainer up. Let me wait for the app to boot inside and verify health + SPA:\\nContainer boots and serves. Now let me verify a real chat message works through the container (RubyLLM \\u2192 OpenRouter \\u2192 Claude):\\nFull chat works through the container \\u2014 Claude replied \\\"DUCK\\\" as requested. All three steps validated. Let me bring down the stack and run a final test sweep to confirm nothing regressed:\\nAll green. Final secret scan + verify entrypoint is executable:\\nPhase 2 validation complete. All steps pass end-to-end.\\n\\n## Validation results\\n\\n**1. Local app boots and runs** \\u2705\\n- Server boots in ~2s; `/up` health \\u2192 200; SPA renders (\\\"RubyLLM Chat\\\", empty state)\\n- **Real chat works**: posted \\\"Say hello in exactly 3 words\\\" \\u2192 Claude Sonnet replied \\\"Hello there, friend!\\\" via OpenRouter/RubyLLM (200 OK in 1890ms, with CSRF token + session cookie)\\n\\n**2. `docker build` finishes** \\u2705\\n- Multi-stage build succeeds; assets precompiled inside the container (esbuild + Tailwind); final image `rubyllm-chat:latest`\\n\\n**3. `docker compose up --build` runs** \\u2705\\n- Container serves on port 80; health \\u2192 200; SPA renders\\n- **Real chat through the container**: posted \\\"Reply with exactly: DUCK\\\" \\u2192 assistant bubble contains \\\"DUCK\\\"\\n\\n## Fix applied during validation\\n\\nThe production container crashed on boot with `Missing secret_key_base for 'production' environment`. Fixed `bin/docker-entrypoint` to auto-generate a random `SECRET_KEY_BASE` at startup when none is provided \\u2014 no secret is committed to any file (compose/Dockerfile/source).\\n\\n## Final CI state (all green)\\n\\n| Check | Result |\\n|-------|--------|\\n| Minitest | 26 runs, 59 assertions, 0 failures, **97.66% coverage** |\\n| RuboCop | no offenses |\\n| Brakeman | 0 security warnings |\\n| bundle-audit | no vulnerabilities |\\n| Secret scan | no real keys in repo |\",\n  \"command\": [\n    \"opencode\",\n    \"run\",\n    \"--agent\",\n    \"build\",\n    \"--format\",\n    \"json\",\n    \"--dir\",\n    \"/mnt/data/Projects/llm-coding-benchmark/results/glm_5_2/project\",\n    \"--session\",\n    \"ses_139708325ffeTky64xJTsqvSXw\",\n    \"Once finished coding and testing, you must make sure it runs, both locally, and that docker build also finishes successfully, and docker compose is able to run.\\n\\nDo not ask for confirmation. Do not stop with a plan. Fulfill the request and finish.\\n\\nThis is phase 2 of 2 and a continuation of the existing project in the current working directory. Do not regenerate the app. Do not create a second app. Validate and fix the current codebase in place.\\n\\nUse environment variables so RubyLLM actually works. Source ~/.config/zsh/secrets only to load the required environment, especially OPENROUTER_API_KEY. Do not print secret values, do not copy secret file contents into the repo, and do not commit secrets into files, logs, Dockerfiles, compose files, or README examples.\\n\\nValidate the project end-to-end in this order:\\n- run the local app in a way that proves it boots\\n- make any fixes needed so it boots cleanly\\n- make sure `docker build` finishes successfully\\n- make sure `docker compose up --build` is able to run\\n\\nIf one step passes, move to the next without asking for confirmation. If something fails, fix it and continue. Only stop when you have actually completed the validation work or you hit a hard blocker you cannot resolve from inside the workspace.\"\n  ],\n  \"continued_from_session\": \"ses_139708325ffeTky64xJTsqvSXw\",\n  \"elapsed_seconds\": 2602.5,\n  \"ended_at\": \"2026-06-14T15:19:15+00:00\",\n  \"exit_code\": 0,\n  \"finish_reason\": \"stop\",\n  \"followup_prompt_sha256\": \"e2f60835f36832ba1242d6f23a02bd7958611c52f2db122a3df93f8727dab9b5\",\n  \"model\": {\n    \"id\": \"zai/glm-5.2\",\n    \"label\": \"GLM 5.2\",\n    \"provider\": \"zai\",\n    \"selection_reason\": \"Z.ai's newest flagship GLM (released 2026-06). Served on the coding plan endpoint at https://api.z.ai/api/coding/paas/v4 (live and key-verified 2026-06-14, though not yet in that endpoint's /models listing; not on OpenRouter yet). Like all GLM models it returns reasoning in reasoning_content with empty content by default \\u2014 the zai provider wiring already handles this for GLM 5.1. Tests whether 5.2 fixes 5.1's hallucinated chat.user/chat.assistant multi-turn DSL (the bug that put 5.1 in Tier C).\",\n    \"slug\": \"glm_5_2\"\n  },\n  \"no_progress_timeout_seconds\": 360,\n  \"opencode_session_id\": \"ses_139708325ffeTky64xJTsqvSXw\",\n  \"output_tokens_per_second\": 0.57,\n  \"paths\": {\n    \"followup_prompt\": \"results/glm_5_2/followup-prompt.txt\",\n    \"followup_stderr\": \"results/glm_5_2/followup-opencode-stderr.log\",\n    \"followup_stdout\": \"results/glm_5_2/followup-opencode-output.ndjson\",\n    \"opencode_config\": \"config/opencode.benchmark.json\",\n    \"project_dir\": \"results/glm_5_2/project\",\n    \"prompt\": \"results/glm_5_2/prompt.txt\",\n    \"session_export\": \"results/glm_5_2/session-export.json\",\n    \"stderr\": \"results/glm_5_2/opencode-stderr.log\",\n    \"stdout\": \"results/glm_5_2/opencode-output.ndjson\"\n  },\n  \"phase\": \"phase2\",\n  \"phases\": [\n    {\n      \"assistant_output_excerpt\": \"I'll build this Rails app. Let me start with a quick plan, then implement.\\n\\n**Plan:**\\n1. Ruby 4.0.5 + Rails 8.1.3 (newest in mise), `--skip-active-record --skip-action-mailer --skip-active-job`\\n2. RubyLLM \\u2192 OpenRouter \\u2192 latest Claude Sonnet, configured via env vars\\n3. SPA: single chat page, Stimulus + Turbo Streams, Tailwind, partials/components\\n4. In-memory conversation store (no DB), streaming responses\\n5. Minitest unit tests per component\\n6. Brakeman, RuboCop, SimpleCov, bundle-audit\\n7. README + Dockerfile + docker-compose\\n\\nLet me begin.\\nVersions confirmed: Ruby 4.0.5, Rails 8.1.3, RubyLLM 1.16.0, model `anthropic/claude-sonnet-4.6`. Now generating the app.\\nApp generated. Let me verify structure and check the Gemfile.\\nRails 8.1 already bundles Brakeman, RuboCop, and bundle-audit. Now I'll add RubyLLM and SimpleCov.\\nGems added. Let me inspect the RubyLLM API to use correct methods (avoid hallucinated APIs).\\nThe shell defaults to Ruby 3.4.8 but mise.toml wants 4.0.5. Let me make everything consistent on 4.0.5 (newest).\\nRuby 4.0.5 + RubyLLM 1.16.0 confirmed. Now let me study the actual RubyLLM API to avoid hallucinated methods.\\nOpenRouter uses `openrouter_api_key`. Now let me study the Chat API.\\nI have a complete understanding of the RubyLLM API. Now let me build the app. Let me check the current config and structure first.\\nNow let me verify the secrets file exists (without printing contents) and check routes.\\nSecrets and env are set. Let me set up a task list and build systematically.\\nNow creating the RubyLLM initializer:\\nNow the app config to disable session store needing a DB and set cache:\\nNow the domain models. Creating Message PORO:\\nLet me verify how RubyLLM's `add_message` and `Message` accept hashes before writing the service.\\nNow the ChatService that wraps RubyLLM cleanly:\\nRoutes:\\nLet me simplify the routes \\u2014 one conversation per session:\\nNow a concern to share conversation lookup, then the controllers:\\nI referenced `ActiveRecord::RecordNotFound` but Active Record is skipped. Let me fix the controller to be clean:\\nNow the views. Let me check the current layout and assets:\\nNow I'll build the componentized UI. First, the layout:\\nNow the chat shell view:\\nNow the message partials:\\nNow the Turbo Stream templates:\\nNow the Stimulus controllers. First, remove the sample hello controller and create real ones:\\nNow wire up the form actions. Let me update the form partial:\\nNow componentize the CSS into separate files (avoid single monolithic stylesheet):\\nLet me check the ApplicationController and ensure `SecureRandom` is available:\\nNow let me build the CSS and JS to verify they compile:\\nnode_modules missing. Let me install JS dependencies:\\nThe generator's `yarn add` calls failed silently (no yarn). Let me install the needed JS deps via npm:\\nNow build the assets:\\nCSS built. JS failed because `index.js` still references the deleted hello controller. Let me fix it:\\nBoth bundles build cleanly. Let me update todos and write tests, then do a boot check.\\nLet me check the test setup and write tests for each component:\\nSet up test_helper with SimpleCov:\\nNow the model tests:\\nNow the ChatService test with a mock RubyLLM client:\\nNow controller tests:\\nThe session-reading helper is fragile (encrypted cookie). Let me simplify that test to inspect the store directly:\\nMy `find` takes an id, not a block. Let me fix the test to check store count instead:\\nNow let me run the test suite to catch issues early:\\nActiveModel doesn't have an `:array` type. Let me fix the Conversation model:\\nNeed to require `minitest/mock` for the `stub` method. Let me fix the test helper:\\nMinitest 6 removed mocks. I'll use clean dependency injection via a class attribute instead. Let me refactor the controller:\\nNow rewrite the controller test to use the injectable service:\\nRemove the invalid `minitest/mock` require from test_helper:\\nAll 26 tests pass, 97.66% coverage. Now CI tooling. Let me update todos and run the linters.\\nRubocop found spacing offenses. Let me autocorrec\",\n      \"command\": [\n        \"opencode\",\n        \"run\",\n        \"--agent\",\n        \"build\",\n        \"--format\",\n        \"json\",\n        \"--dir\",\n        \"/mnt/data/Projects/llm-coding-benchmark/results/glm_5_2/project\",\n        \"-m\",\n        \"zai/glm-5.2\",\n        \"I want you to build a Ruby on Rails application. Use the newest Ruby and Rails available in mise here; you have access to mise. First make a short implementation plan for yourself, then go ahead with the implementation without asking for confirmation. Do not stop to ask what to do next, do not answer with only a plan, and do not ask whether you should start creating files.\\n\\nUse only the tools available in this runtime. Do not call apply_patch. For file changes, use edit for existing files and write for new files. If a tool call fails, recover and continue implementing instead of stopping.\\n\\nUse the Rails generators to generate the initial code for the project. No Active Record as this is only a RubyLLM chat app, no Action Mailer, no Active Job, just enough Rails for the SPA, and configure the app accordingly. You will make a very simple SPA mimicking a minimal ChatGPT-like web interface. Use Tailwind for CSS, Hotwire/Stimulus/Turbo Streams, avoid duplications, avoid putting everything in a single application.css or application.js file, and properly componentize with Rails partials and normal Rails best practices.\\n\\nYou must use environment variables so RubyLLM actually works. Source ~/.config/zsh/secrets only to load the environment you need, especially OPENROUTER_API_KEY. Do not print secret values, do not copy secret file contents into the repo, and do not commit secrets into source files, .env files, Dockerfiles, compose files, logs, or README examples.\\n\\nUse the latest RubyLLM and configure it to connect to OpenRouter and use the latest Claude Sonnet for the chat. Add proper Minitest unit tests for each component. Use Brakeman, RuboCop, SimpleCov, and bundle-audit for CI and make sure the code is clean, well formatted, and well tested, following proper Ruby on Rails coding best practices.\\n\\nThis app will not have authentication. It is really a simple webpage for RubyLLM. Document the project in a README.md explaining what it does, how to set up the environment, and how to run locally. Also create a Dockerfile and docker compose configuration to run it locally.\\n\\nThis is phase 1 of 2. Focus on implementation, tests, and project structure. Do not spend time on full runtime validation beyond what is needed to keep implementation moving.\\n\\nStay inside the current workspace and modify the current project only. Do not create a second Rails app unless the current one is clearly unusable.\"\n      ],\n      \"continued_from_session\": null,\n      \"elapsed_seconds\": 1992.92,\n      \"ended_at\": \"2026-06-14T15:09:05+00:00\",\n      \"exit_code\": 0,\n      \"finish_reason\": \"stop\",\n      \"model\": {\n        \"id\": \"zai/glm-5.2\",\n        \"label\": \"GLM 5.2\",\n        \"provider\": \"zai\",\n        \"selection_reason\": \"Z.ai's newest flagship GLM (released 2026-06). Served on the coding plan endpoint at https://api.z.ai/api/coding/paas/v4 (live and key-verified 2026-06-14, though not yet in that endpoint's /models listing; not on OpenRouter yet). Like all GLM models it returns reasoning in reasoning_content with empty content by default \\u2014 the zai provider wiring already handles this for GLM 5.1. Tests whether 5.2 fixes 5.1's hallucinated chat.user/chat.assistant multi-turn DSL (the bug that put 5.1 in Tier C).\",\n        \"slug\": \"glm_5_2\"\n      },\n      \"no_progress_timeout_seconds\": 360,\n      \"opencode_session_id\": \"ses_139708325ffeTky64xJTsqvSXw\",\n      \"output_tokens_per_second\": 0.22,\n      \"paths\": {\n        \"opencode_config\": \"config/opencode.benchmark.json\",\n        \"project_dir\": \"results/glm_5_2/project\",\n        \"prompt\": \"results/glm_5_2/prompt.txt\",\n        \"stderr\": \"results/glm_5_2/opencode-stderr.log\",\n        \"stdout\": \"results/glm_5_2/opencode-output.ndjson\"\n      },\n      \"phase\": \"phase1\",\n      \"preview_output_tokens_per_second\": 56.0,\n      \"preview_output_tokens_per_second_average\": 65.66,\n      \"project_summary\": {\n        \"file_count\": 810,\n        \"present\": {\n          \"app_dir\": true,\n          \"compose_yaml\": false,\n          \"compose_yml\": false,\n          \"docker_compose_yaml\": false,\n          \"docker_compose_yml\": true,\n          \"dockerfile\": true,\n          \"gemfile\": true,\n          \"javascript_dir\": true,\n          \"readme_lower\": false,\n          \"readme_md\": true,\n          \"routes\": true,\n          \"tests_dir\": true,\n          \"views_dir\": true\n        },\n        \"works_as_intended\": \"yes\",\n        \"works_note\": \"Rails app, tests, README, and container files detected.\"\n      },\n      \"prompt_sha256\": \"d25f119447215ebf47477c1ce61b24f801bfcb9336467f5b019d554f3c83537c\",\n      \"stall_reason\": null,\n      \"stalled\": false,\n      \"started_at\": \"2026-06-14T14:35:52+00:00\",\n      \"status\": \"completed\",\n      \"stderr_excerpt\": \"\",\n      \"timed_out\": false,\n      \"timeout_seconds\": 5400,\n      \"tokens\": {\n        \"cache\": {\n          \"read\": 79424,\n          \"write\": 0\n        },\n        \"input\": 669,\n        \"output\": 430,\n        \"reasoning\": 0,\n        \"total\": 80523\n      },\n      \"tokens_per_second\": 40.4\n    },\n    {\n      \"assistant_output_excerpt\": \"Phase 2: end-to-end validation. Let me start by ensuring a clean state, then validate in order: local boot \\u2192 docker build \\u2192 docker compose.\\nRepo is clean. Let me first kill any lingering puma processes safely, then validate local boot.\\nThe `pkill -f puma` matches its own command string. Let me find and kill by PID instead:\\nShell is alive. Let me check running processes without killing:\\nNo lingering processes. Now step 1: validate local boot. I'll start the server in the background with proper PID management and a hard timeout to avoid hangs:\\nLocal boot passes (server up in 2s, health 200, SPA renders). Now let me validate a real chat message works end-to-end (RubyLLM \\u2192 OpenRouter \\u2192 Claude):\\nLet me inspect that response more carefully \\u2014 186KB is large. Let me check the log and response content:\\nCSRF protection is rejecting the bare curl POST (expected \\u2014 a real browser sends the token via Turbo). Let me simulate a real browser by extracting the CSRF token and cookie first:\\nLocal app fully validated \\u2014 real chat works: Claude Sonnet replied \\\"Hello there, friend!\\\" via OpenRouter/RubyLLM (200 OK in 1890ms). \\n\\nNow **step 2: docker build**. Let me verify prerequisites and run it:\\nDocker build succeeded \\u2014 image `rubyllm-chat:latest` built, assets precompiled inside the container. \\n\\nNow **step 3: docker compose up --build**. Let me source secrets and run it, then verify the container serves:\\nPort 80 is free and compose config resolves the key. (I'll avoid `compose config` going forward since it prints the key.) Now let me run `docker compose up --build`:\\nContainer started. Let me wait for the app to boot inside, then verify it serves correctly:\\nConnection failed (000). Let me check the container logs to diagnose:\\nThe app crashed on boot. Let me see the actual error at the top of the logs:\\nThe container crashes in production because `secret_key_base` is missing. I'll fix the entrypoint to auto-generate one at startup if not provided (no secret committed). Let me stop the container first:\\nNow fix the entrypoint to auto-generate `SECRET_KEY_BASE`:\\nNow rebuild and re-run docker compose:\\nContainer up. Let me wait for the app to boot inside and verify health + SPA:\\nContainer boots and serves. Now let me verify a real chat message works through the container (RubyLLM \\u2192 OpenRouter \\u2192 Claude):\\nFull chat works through the container \\u2014 Claude replied \\\"DUCK\\\" as requested. All three steps validated. Let me bring down the stack and run a final test sweep to confirm nothing regressed:\\nAll green. Final secret scan + verify entrypoint is executable:\\nPhase 2 validation complete. All steps pass end-to-end.\\n\\n## Validation results\\n\\n**1. Local app boots and runs** \\u2705\\n- Server boots in ~2s; `/up` health \\u2192 200; SPA renders (\\\"RubyLLM Chat\\\", empty state)\\n- **Real chat works**: posted \\\"Say hello in exactly 3 words\\\" \\u2192 Claude Sonnet replied \\\"Hello there, friend!\\\" via OpenRouter/RubyLLM (200 OK in 1890ms, with CSRF token + session cookie)\\n\\n**2. `docker build` finishes** \\u2705\\n- Multi-stage build succeeds; assets precompiled inside the container (esbuild + Tailwind); final image `rubyllm-chat:latest`\\n\\n**3. `docker compose up --build` runs** \\u2705\\n- Container serves on port 80; health \\u2192 200; SPA renders\\n- **Real chat through the container**: posted \\\"Reply with exactly: DUCK\\\" \\u2192 assistant bubble contains \\\"DUCK\\\"\\n\\n## Fix applied during validation\\n\\nThe production container crashed on boot with `Missing secret_key_base for 'production' environment`. Fixed `bin/docker-entrypoint` to auto-generate a random `SECRET_KEY_BASE` at startup when none is provided \\u2014 no secret is committed to any file (compose/Dockerfile/source).\\n\\n## Final CI state (all green)\\n\\n| Check | Result |\\n|-------|--------|\\n| Minitest | 26 runs, 59 assertions, 0 failures, **97.66% coverage** |\\n| RuboCop | no offenses |\\n| Brakeman | 0 security warnings |\\n| bundle-audit | no vulnerabilities |\\n| Secret scan | no real keys in repo |\",\n      \"command\": [\n        \"opencode\",\n        \"run\",\n        \"--agent\",\n        \"build\",\n        \"--format\",\n        \"json\",\n        \"--dir\",\n        \"/mnt/data/Projects/llm-coding-benchmark/results/glm_5_2/project\",\n        \"--session\",\n        \"ses_139708325ffeTky64xJTsqvSXw\",\n        \"Once finished coding and testing, you must make sure it runs, both locally, and that docker build also finishes successfully, and docker compose is able to run.\\n\\nDo not ask for confirmation. Do not stop with a plan. Fulfill the request and finish.\\n\\nThis is phase 2 of 2 and a continuation of the existing project in the current working directory. Do not regenerate the app. Do not create a second app. Validate and fix the current codebase in place.\\n\\nUse environment variables so RubyLLM actually works. Source ~/.config/zsh/secrets only to load the required environment, especially OPENROUTER_API_KEY. Do not print secret values, do not copy secret file contents into the repo, and do not commit secrets into files, logs, Dockerfiles, compose files, or README examples.\\n\\nValidate the project end-to-end in this order:\\n- run the local app in a way that proves it boots\\n- make any fixes needed so it boots cleanly\\n- make sure `docker build` finishes successfully\\n- make sure `docker compose up --build` is able to run\\n\\nIf one step passes, move to the next without asking for confirmation. If something fails, fix it and continue. Only stop when you have actually completed the validation work or you hit a hard blocker you cannot resolve from inside the workspace.\"\n      ],\n      \"continued_from_session\": \"ses_139708325ffeTky64xJTsqvSXw\",\n      \"elapsed_seconds\": 609.58,\n      \"ended_at\": \"2026-06-14T15:19:14+00:00\",\n      \"exit_code\": 0,\n      \"finish_reason\": \"stop\",\n      \"model\": {\n        \"id\": \"zai/glm-5.2\",\n        \"label\": \"GLM 5.2\",\n        \"provider\": \"zai\",\n        \"selection_reason\": \"Z.ai's newest flagship GLM (released 2026-06). Served on the coding plan endpoint at https://api.z.ai/api/coding/paas/v4 (live and key-verified 2026-06-14, though not yet in that endpoint's /models listing; not on OpenRouter yet). Like all GLM models it returns reasoning in reasoning_content with empty content by default \\u2014 the zai provider wiring already handles this for GLM 5.1. Tests whether 5.2 fixes 5.1's hallucinated chat.user/chat.assistant multi-turn DSL (the bug that put 5.1 in Tier C).\",\n        \"slug\": \"glm_5_2\"\n      },\n      \"no_progress_timeout_seconds\": 360,\n      \"opencode_session_id\": \"ses_139708325ffeTky64xJTsqvSXw\",\n      \"output_tokens_per_second\": 0.57,\n      \"paths\": {\n        \"opencode_config\": \"config/opencode.benchmark.json\",\n        \"project_dir\": \"results/glm_5_2/project\",\n        \"prompt\": \"results/glm_5_2/followup-prompt.txt\",\n        \"stderr\": \"results/glm_5_2/followup-opencode-stderr.log\",\n        \"stdout\": \"results/glm_5_2/followup-opencode-output.ndjson\"\n      },\n      \"phase\": \"phase2\",\n      \"preview_output_tokens_per_second\": 55.62,\n      \"preview_output_tokens_per_second_average\": 442.19,\n      \"project_summary\": {\n        \"file_count\": 811,\n        \"present\": {\n          \"app_dir\": true,\n          \"compose_yaml\": false,\n          \"compose_yml\": false,\n          \"docker_compose_yaml\": false,\n          \"docker_compose_yml\": true,\n          \"dockerfile\": true,\n          \"gemfile\": true,\n          \"javascript_dir\": true,\n          \"readme_lower\": false,\n          \"readme_md\": true,\n          \"routes\": true,\n          \"tests_dir\": true,\n          \"views_dir\": true\n        },\n        \"works_as_intended\": \"yes\",\n        \"works_note\": \"Rails app, tests, README, and container files detected.\"\n      },\n      \"prompt_sha256\": \"e2f60835f36832ba1242d6f23a02bd7958611c52f2db122a3df93f8727dab9b5\",\n      \"stall_reason\": null,\n      \"stalled\": false,\n      \"started_at\": \"2026-06-14T15:09:05+00:00\",\n      \"status\": \"completed\",\n      \"stderr_excerpt\": \"\",\n      \"timed_out\": false,\n      \"timeout_seconds\": 5400,\n      \"tokens\": {\n        \"cache\": {\n          \"read\": 91648,\n          \"write\": 0\n        },\n        \"input\": 435,\n        \"output\": 347,\n        \"reasoning\": 0,\n        \"total\": 92430\n      },\n      \"tokens_per_second\": 151.63\n    }\n  ],\n  \"preview_output_tokens_per_second\": 55.62,\n  \"preview_output_tokens_per_second_average\": 442.19,\n  \"primary_prompt_sha256\": \"d25f119447215ebf47477c1ce61b24f801bfcb9336467f5b019d554f3c83537c\",\n  \"project_summary\": {\n    \"file_count\": 811,\n    \"present\": {\n      \"app_dir\": true,\n      \"compose_yaml\": false,\n      \"compose_yml\": false,\n      \"docker_compose_yaml\": false,\n      \"docker_compose_yml\": true,\n      \"dockerfile\": true,\n      \"gemfile\": true,\n      \"javascript_dir\": true,\n      \"readme_lower\": false,\n      \"readme_md\": true,\n      \"routes\": true,\n      \"tests_dir\": true,\n      \"views_dir\": true\n    },\n    \"works_as_intended\": \"yes\",\n    \"works_note\": \"Rails app, tests, README, and container files detected.\"\n  },\n  \"prompt_sha256\": \"e2f60835f36832ba1242d6f23a02bd7958611c52f2db122a3df93f8727dab9b5\",\n  \"session_exported\": true,\n  \"stall_reason\": null,\n  \"stalled\": false,\n  \"started_at\": \"2026-06-14T15:09:05+00:00\",\n  \"status\": \"completed\",\n  \"stderr_excerpt\": \"\",\n  \"timed_out\": false,\n  \"timeout_seconds\": 5400,\n  \"tokens\": {\n    \"cache\": {\n      \"read\": 91648,\n      \"write\": 0\n    },\n    \"input\": 435,\n    \"output\": 347,\n    \"reasoning\": 0,\n    \"total\": 92430\n  },\n  \"tokens_per_second\": 151.63\n}\n"}}, "config/models.json": {"4ad84ee9510a59ddd101e621b23d6210358994b7": {"t": 1785674167.592636, "n": 45070, "h": "b14957aec71b0ffa", "c": "{\n  \"runner\": {\n    \"command\": \"opencode\",\n    \"args\": [\n      \"run\",\n      \"--agent\",\n      \"build\",\n      \"--format\",\n      \"json\"\n    ],\n    \"notes\": [\n      \"Selected after local probing because it exposes machine-readable JSON events with session IDs and token counts.\",\n      \"The local crush install advertised --yolo in help output but rejected the flag at runtime, which makes it a poor default for unattended benchmarking here.\",\n      \"The explicit build agent has permissive filesystem/tool rules, which is the closest match to the requested autonomous coding workflow.\"\n    ]\n  },\n  \"models\": [\n    {\n      \"slug\": \"gemma4_31b\",\n      \"id\": \"ollama/google/gemma4-31b-it-bf16\",\n      \"label\": \"Gemma 4 31B\",\n      \"provider\": \"ollama\",\n      \"skip_by_default\": true,\n      \"benchmark_context_override\": 98304,\n      \"llama_swap_model\": \"gemma4:27b\",\n      \"selection_reason\": \"Hosted locally via llama-swap. Requires llama.cpp b8665+ for the dedicated Gemma 4 tool call parser (PR #21418). Skipped by default; re-enable for llama-swap benchmark runs.\"\n    },\n    {\n      \"slug\": \"glm_4_7_flash_bf16\",\n      \"id\": \"ollama/glm/glm-4.7-flash-bf16\",\n      \"label\": \"GLM 4.7 Flash BF16\",\n      \"provider\": \"ollama\",\n      \"skip_by_default\": true,\n      \"benchmark_context_override\": 100000,\n      \"llama_swap_model\": \"glm-4.7-flash:q8\",\n      \"selection_reason\": \"Hosted locally via llama-swap. Needs --jinja --reasoning-format none to suppress <think> tags in content. Tool calling works correctly with these flags.\"\n    },\n    {\n      \"slug\": \"llama4_scout\",\n      \"id\": \"ollama/meta/llama4-scout\",\n      \"label\": \"Llama 4 Scout\",\n      \"provider\": \"ollama\",\n      \"skip_by_default\": true,\n      \"llama_swap_model\": \"llama4:scout\",\n      \"selection_reason\": \"Hosted locally via llama-swap. Skipped by default: llama.cpp has no parser for Llama 4's pythonic tool call format \\u2014 model outputs tool calls as plain text content instead of structured tool_calls. Requires upstream llama.cpp support (similar to vLLM's llama4_pythonic parser).\"\n    },\n    {\n      \"slug\": \"qwen3_32b\",\n      \"id\": \"ollama/qwen/qwen3-32b\",\n      \"label\": \"Qwen 3 32B\",\n      \"provider\": \"ollama\",\n      \"llama_swap_model\": \"qwen3:32b\",\n      \"selection_reason\": \"Requested local model family; exact hosted variant available through opencode. Superseded by the Qwen 3.5 line for future local benchmarking. Skipped by default after benchmark preview averaged 7.96 output tok/s over the first 3 steps (< 20.00).\",\n      \"skip_by_default\": true\n    },\n    {\n      \"slug\": \"qwen3_coder_next\",\n      \"id\": \"ollama/qwen/qwen3-coder-next\",\n      \"label\": \"Qwen 3 Coder Next\",\n      \"provider\": \"ollama\",\n      \"llama_swap_model\": \"qwen3-coder:30b\",\n      \"selection_reason\": \"Best direct coding-oriented local Qwen variant matching the original benchmark brief. Skipped by default after benchmark preview measured 6.59 output tok/s (< 20.00).\",\n      \"skip_by_default\": true\n    },\n    {\n      \"slug\": \"qwen3_5_35b\",\n      \"id\": \"ollama/qwen/qwen3.5-35b\",\n      \"label\": \"Qwen 3.5 35B\",\n      \"provider\": \"ollama\",\n      \"skip_by_default\": true,\n      \"llama_swap_model\": \"qwen3.5:35b\",\n      \"selection_reason\": \"Requested local model family; exact hosted variant available through opencode. Skipped by default because the current benchmark pass is restricted to OpenRouter models that previously completed successfully.\"\n    },\n    {\n      \"slug\": \"qwen3_6_35b\",\n      \"id\": \"ollama/qwen/qwen3.6-35b\",\n      \"label\": \"Qwen 3.6 35B\",\n      \"provider\": \"ollama\",\n      \"skip_by_default\": true,\n      \"llama_swap_model\": \"qwen3.6:35b\",\n      \"selection_reason\": \"Qwen 3.6 35B-A3B (released 2026-04-15). Same qwen3_5_moe architecture as 3.5 (35B total / 3B active MoE). Q3_K_M ~16 GB \\u2014 drop-in replacement for 3.5. Significant benchmark gains: SWE-bench 73.4 (was 70), Terminal-Bench 51.5 (was 40.5), MCPMark 37 (was 27). Has vision encoder. Same chat template and llama.cpp flags as 3.5.\"\n    },\n    {\n      \"slug\": \"qwen3_5_122b\",\n      \"id\": \"ollama/qwen/qwen3.5-122b\",\n      \"label\": \"Qwen 3.5 122B\",\n      \"provider\": \"ollama\",\n      \"selection_reason\": \"Hosted locally via llama-swap. Needs --reasoning-format none on llama-server to avoid reasoning_content tokens that some clients mishandle. Tool calling works correctly with Qwen chat template.\",\n      \"benchmark_context_override\": 150000,\n      \"llama_swap_model\": \"qwen3.5:122b\",\n      \"skip_by_default\": true\n    },\n    {\n      \"slug\": \"gpt_oss_20b\",\n      \"id\": \"ollama/openai/gpt-oss-20b\",\n      \"label\": \"GPT OSS 20B\",\n      \"provider\": \"ollama\",\n      \"skip_by_default\": true,\n      \"llama_swap_model\": \"gpt-oss:20b\",\n      \"selection_reason\": \"Added as a local Ollama GPT OSS baseline for later warmup and benchmark testing.\"\n    },\n    {\n      \"slug\": \"nemotron_cascade_2\",\n      \"id\": \"ollama/nemotron_cascade_2\",\n      \"label\": \"Nemotron Cascade 2\",\n      \"provider\": \"ollama\",\n      \"skip_by_default\": true,\n      \"ollama_model_name\": \"nemotron-cascade-2:latest\",\n      \"llama_swap_model\": \"nemotron-cascade-2:latest\",\n      \"ollama_limit_context\": 262144,\n      \"ollama_limit_output\": 32768,\n      \"ollama_tool_call\": true,\n      \"ollama_reasoning\": true,\n      \"selection_reason\": \"Added as a local Ollama Nemotron Cascade 2 candidate for later warmup and benchmark testing. This entry uses explicit local model metadata because it is not yet mapped in the home opencode config.\"\n    },\n    {\n      \"slug\": \"claude_opus_4_6\",\n      \"id\": \"openrouter/anthropic/claude-opus-4.6\",\n      \"label\": \"Claude Opus 4.6\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"Exact requested cloud model.\"\n    },\n    {\n      \"slug\": \"claude_opus_4_7\",\n      \"id\": \"openrouter/anthropic/claude-opus-4.7\",\n      \"label\": \"Claude Opus 4.7\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"Anthropic Claude Opus 4.7 on OpenRouter. Built for long-running async agents. Same pricing as 4.6: $5/M input, $25/M output. 1M context, 128K max output. Released 2026-04-16.\"\n    },\n    {\n      \"slug\": \"claude_opus_4_8\",\n      \"id\": \"openrouter/anthropic/claude-opus-4.8\",\n      \"label\": \"Claude Opus 4.8\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"Anthropic Claude Opus 4.8 on OpenRouter. Direct successor to Opus 4.7 using the regular (non-fast) endpoint. 1M context, tool calling supported, $5/M input and $25/M output. Tests whether the 4.8 release keeps Opus 4.7's benchmark-leading RubyLLM correctness while improving speed or implementation discipline.\"\n    },\n    {\n      \"slug\": \"claude_fable_5\",\n      \"id\": \"openrouter/anthropic/claude-fable-5\",\n      \"label\": \"Claude Fable 5\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"Anthropic Claude Fable 5 on OpenRouter (snapshot claude-5-fable-20260609, released 2026-06). New Claude 5-generation model. 1M context, tool calling supported, $10/M input and $50/M output \\u2014 2x Opus 4.x pricing. Tests whether the new generation improves on Opus 4.7/4.8's benchmark-leading RubyLLM correctness.\"\n    },\n    {\n      \"slug\": \"claude_fable_5_rerelease\",\n      \"id\": \"openrouter/anthropic/claude-fable-5\",\n      \"label\": \"Claude Fable 5 (re-release)\",\n      \"provider\": \"openrouter\",\n      \"skip_by_default\": true,\n      \"selection_reason\": \"Anthropic Claude Fable 5 re-release on OpenRouter, tested separately from the original 2026-06 claude_fable_5 run after the model was removed and re-released. Uses the same concrete model ID so the old result remains intact while measuring whether the new serving snapshot regressed in RubyLLM/Rails benchmark behavior.\"\n    },\n    {\n      \"slug\": \"claude_sonnet_5\",\n      \"id\": \"openrouter/anthropic/claude-sonnet-5\",\n      \"label\": \"Claude Sonnet 5\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"Anthropic Claude Sonnet 5 on OpenRouter, released 2026-06-30. Direct successor to Sonnet 4.6 with 1M context, tool calling, and adaptive thinking. Tests whether the Claude 5-generation Sonnet tier catches up to Opus/Fable on RubyLLM API correctness while remaining cheaper than Opus-class models.\"\n    },\n    {\n      \"slug\": \"opencode_opus_glm\",\n      \"id\": \"openrouter/anthropic/claude-opus-4.7\",\n      \"label\": \"opencode Opus 4.7 + GLM 5.1 coder\",\n      \"provider\": \"openrouter\",\n      \"skip_by_default\": true,\n      \"opencode_subagent\": {\n        \"name\": \"coder\",\n        \"model_id\": \"zai/glm-5.1\",\n        \"provider\": \"zai\",\n        \"description\": \"Use proactively for concrete coding execution: file edits, refactors, bug fixes, test writing, boilerplate generation, single-file implementations. The primary (Opus) plans and delegates; this agent (GLM 5.1) executes cheaply. Skip delegation for cross-file architectural decisions or debugging with unclear root cause.\",\n        \"prompt\": \"You are a focused coding agent. The parent (Opus) has already decided the approach \\u2014 your job is to execute cleanly. Follow instructions precisely. Don't re-plan or second-guess. Match existing codebase style. Keep changes minimal \\u2014 do what was asked, nothing more. Default to no comments.\"\n      },\n      \"selection_reason\": \"opencode multi-agent: Opus 4.7 primary + GLM 5.1 (Z.ai) coding subagent. Tests whether the cost-effective Chinese model handles coding when Opus plans. GLM 5.1 via Z.ai coding plan endpoint (subscription). Comparable to Claude Code's opus+sonnet variant but with a non-Anthropic coder.\"\n    },\n    {\n      \"slug\": \"opencode_opus_glm_forced\",\n      \"id\": \"openrouter/anthropic/claude-opus-4.7\",\n      \"label\": \"opencode Opus 4.7 + GLM 5.1 coder (FORCED delegation)\",\n      \"provider\": \"openrouter\",\n      \"skip_by_default\": true,\n      \"opencode_subagent\": {\n        \"name\": \"coder\",\n        \"model_id\": \"zai/glm-5.1\",\n        \"provider\": \"zai\",\n        \"description\": \"Use for all concrete coding execution dispatched by the planner-orchestrator. The planner will give you full context per subtask.\",\n        \"prompt\": \"You are a focused coding agent. Execute the dispatched subtask exactly as specified. Follow the provided instructions, file paths, and acceptance criteria literally. Keep changes minimal \\u2014 only do what the subtask describes. Match existing codebase style.\"\n      },\n      \"selection_reason\": \"Forced-delegation variant of opencode_opus_glm. Runs with prompts/benchmark_prompt_forced_delegation.txt. Measures whether forcing the orchestrator pattern produces usable code via Opus (plan) + GLM 5.1 (execute) vs the free-choice version which didn't delegate at all.\"\n    },\n    {\n      \"slug\": \"opencode_opus_kimi_forced\",\n      \"id\": \"openrouter/anthropic/claude-opus-4.7\",\n      \"label\": \"opencode Opus 4.7 + Kimi K2.6 coder (FORCED delegation)\",\n      \"provider\": \"openrouter\",\n      \"skip_by_default\": true,\n      \"opencode_subagent\": {\n        \"name\": \"coder\",\n        \"model_id\": \"openrouter/moonshotai/kimi-k2.6\",\n        \"provider\": \"openrouter\",\n        \"description\": \"Use for all concrete coding execution dispatched by the planner-orchestrator. The planner will give you full context per subtask.\",\n        \"prompt\": \"You are a focused coding agent. Execute the dispatched subtask exactly as specified. Follow the provided instructions, file paths, and acceptance criteria literally. Keep changes minimal \\u2014 only do what the subtask describes. Match existing codebase style.\"\n      },\n      \"selection_reason\": \"Replacement for opencode_opus_glm_forced after Z.ai GLM 5.1 subagent stalled twice in the forced-delegation experiment. Kimi K2.6 was Tier A (87/100) in the solo benchmark vs GLM 5.1's Tier C (46/100), and both planner+subagent run through OpenRouter (no provider mixing latency). Runs with prompts/benchmark_prompt_forced_delegation.txt.\"\n    },\n    {\n      \"slug\": \"opencode_opus_qwen36plus_forced\",\n      \"id\": \"openrouter/anthropic/claude-opus-4.7\",\n      \"label\": \"opencode Opus 4.7 + Qwen 3.6 Plus coder (FORCED delegation)\",\n      \"provider\": \"openrouter\",\n      \"skip_by_default\": true,\n      \"opencode_subagent\": {\n        \"name\": \"coder\",\n        \"model_id\": \"openrouter/qwen/qwen3.6-plus\",\n        \"provider\": \"openrouter\",\n        \"description\": \"Use for all concrete coding execution dispatched by the planner-orchestrator. The planner will give you full context per subtask.\",\n        \"prompt\": \"You are a focused coding agent. Execute the dispatched subtask exactly as specified. Follow the provided instructions, file paths, and acceptance criteria literally. Keep changes minimal \\u2014 only do what the subtask describes. Match existing codebase style.\"\n      },\n      \"selection_reason\": \"Test the cheap-cloud-executor pairing: Opus plans, Qwen 3.6 Plus (Tier B 71/100 solo via OpenRouter free tier) executes. Same provider lane as planner so should not exhibit the cross-provider task-dispatch stall seen with GLM 5.1 (Z.ai) and local Qwen (llama-swap). Runs with prompts/benchmark_prompt_forced_delegation.txt.\"\n    },\n    {\n      \"slug\": \"opencode_opus_deepseek_forced\",\n      \"id\": \"openrouter/anthropic/claude-opus-4.7\",\n      \"label\": \"opencode Opus 4.7 + DeepSeek V4 Pro coder (FORCED delegation)\",\n      \"provider\": \"openrouter\",\n      \"skip_by_default\": true,\n      \"opencode_subagent\": {\n        \"name\": \"coder\",\n        \"model_id\": \"openrouter/deepseek/deepseek-v4-pro\",\n        \"provider\": \"openrouter\",\n        \"description\": \"Use for all concrete coding execution dispatched by the planner-orchestrator. The planner will give you full context per subtask.\",\n        \"prompt\": \"You are a focused coding agent. Execute the dispatched subtask exactly as specified. Follow the provided instructions, file paths, and acceptance criteria literally. Keep changes minimal \\u2014 only do what the subtask describes. Match existing codebase style.\"\n      },\n      \"selection_reason\": \"Test whether DeepSeek V4 Pro (solo Tier C 69/100 \\u2014 Tier 1 code with Tier 3 deliverables) executes cleanly when Opus handles the planning/integration. Same OpenRouter provider lane to avoid the cross-provider task-dispatch stall. Runs with prompts/benchmark_prompt_forced_delegation.txt.\"\n    },\n    {\n      \"slug\": \"opencode_gpt55_qwen36plus_forced\",\n      \"id\": \"openrouter/openai/gpt-5.5\",\n      \"label\": \"opencode GPT 5.5 + Qwen 3.6 Plus coder (FORCED delegation)\",\n      \"provider\": \"openrouter\",\n      \"skip_by_default\": true,\n      \"opencode_subagent\": {\n        \"name\": \"coder\",\n        \"model_id\": \"openrouter/qwen/qwen3.6-plus\",\n        \"provider\": \"openrouter\",\n        \"description\": \"Use for all concrete coding execution dispatched by the planner-orchestrator. The planner will give you full context per subtask.\",\n        \"prompt\": \"You are a focused coding agent. Execute the dispatched subtask exactly as specified. Follow the provided instructions, file paths, and acceptance criteria literally. Keep changes minimal \\u2014 only do what the subtask describes. Match existing codebase style.\"\n      },\n      \"selection_reason\": \"Stress test: GPT 5.5 (typically Codex-only because OpenAI restricts tool calling on OpenRouter for GPT 5.x) as opencode planner with cheap Qwen executor. KNOWN RISK: GPT 5.5 may not tool-call on OpenRouter; if it can't, the run will fail with no Task dispatches and that itself is a useful finding. Runs with prompts/benchmark_prompt_forced_delegation.txt.\"\n    },\n    {\n      \"slug\": \"opencode_gpt55_deepseek_forced\",\n      \"id\": \"openrouter/openai/gpt-5.5\",\n      \"label\": \"opencode GPT 5.5 + DeepSeek V4 Pro coder (FORCED delegation)\",\n      \"provider\": \"openrouter\",\n      \"skip_by_default\": true,\n      \"opencode_subagent\": {\n        \"name\": \"coder\",\n        \"model_id\": \"openrouter/deepseek/deepseek-v4-pro\",\n        \"provider\": \"openrouter\",\n        \"description\": \"Use for all concrete coding execution dispatched by the planner-orchestrator. The planner will give you full context per subtask.\",\n        \"prompt\": \"You are a focused coding agent. Execute the dispatched subtask exactly as specified. Follow the provided instructions, file paths, and acceptance criteria literally. Keep changes minimal \\u2014 only do what the subtask describes. Match existing codebase style.\"\n      },\n      \"selection_reason\": \"Stress test: GPT 5.5 + DeepSeek V4 Pro both via OpenRouter. KNOWN RISK: GPT 5.5 may lack tool calling on OpenRouter, in which case no delegation will occur. Runs with prompts/benchmark_prompt_forced_delegation.txt.\"\n    },\n    {\n      \"slug\": \"opencode_opus_qwen_forced\",\n      \"id\": \"openrouter/anthropic/claude-opus-4.7\",\n      \"label\": \"opencode Opus 4.7 + Qwen 3.6 local coder (FORCED delegation)\",\n      \"provider\": \"openrouter\",\n      \"skip_by_default\": true,\n      \"opencode_subagent\": {\n        \"name\": \"coder\",\n        \"model_id\": \"ollama/qwen/qwen3.6-35b\",\n        \"provider\": \"ollama\",\n        \"llama_swap_model\": \"qwen3.6:35b\",\n        \"description\": \"Use for all concrete coding execution dispatched by the planner-orchestrator. Runs locally on llama-swap.\",\n        \"prompt\": \"You are a local coding agent running on llama-swap. Execute the dispatched subtask exactly as specified. Follow instructions literally. Keep changes minimal.\"\n      },\n      \"selection_reason\": \"Forced-delegation variant of opencode_opus_qwen. Most interesting test case: expensive cloud orchestrator + free local executor. If this produces working code it's the cheapest usable multi-agent configuration. Depends on llama-swap with qwen3.6:35b loaded.\"\n    },\n    {\n      \"slug\": \"opencode_opus_qwen\",\n      \"id\": \"openrouter/anthropic/claude-opus-4.7\",\n      \"label\": \"opencode Opus 4.7 + Qwen 3.6 local coder\",\n      \"provider\": \"openrouter\",\n      \"skip_by_default\": true,\n      \"opencode_subagent\": {\n        \"name\": \"coder\",\n        \"model_id\": \"ollama/qwen/qwen3.6-35b\",\n        \"provider\": \"ollama\",\n        \"llama_swap_model\": \"qwen3.6:35b\",\n        \"description\": \"Use proactively for concrete coding execution: file edits, refactors, simple implementations. The primary (Opus) plans and delegates; this agent (local Qwen 3.6 via llama-swap) executes locally to save API cost. Skip delegation for complex reasoning or gem-specific API work where cloud models are more reliable.\",\n        \"prompt\": \"You are a local coding agent running on llama-swap. The parent (Opus) has decided the approach \\u2014 just execute. Follow instructions precisely. Match existing codebase style. Keep changes minimal.\"\n      },\n      \"selection_reason\": \"opencode multi-agent: Opus 4.7 primary (cloud) + Qwen 3.6 35B (local llama-swap) coding subagent. Tests the 'local hybrid' hypothesis \\u2014 expensive cloud orchestrator with free local executor. Depends on llama-swap running with qwen3.6:35b loaded.\"\n    },\n    {\n      \"slug\": \"gpt_5_4_pro\",\n      \"id\": \"openrouter/openai/gpt-5.4-pro\",\n      \"label\": \"GPT 5.4 Pro\",\n      \"provider\": \"openrouter\",\n      \"skip_by_default\": true,\n      \"selection_reason\": \"Chosen from the OpenRouter GPT 5.4 family as the largest and most coding-oriented variant. Skipped by default because it failed in the previous benchmark pass.\"\n    },\n    {\n      \"slug\": \"gpt_5_4_codex\",\n      \"id\": \"gpt-5.4\",\n      \"label\": \"GPT 5.4 xHigh (Codex)\",\n      \"provider\": \"codex\",\n      \"runner_type\": \"codex\",\n      \"codex_reasoning_effort\": \"xhigh\",\n      \"selection_reason\": \"GPT 5.4 via Codex CLI at xhigh reasoning effort. Tier 2: correct entry point (RubyLLM.chat + ask + response.content) but add_message uses keyword args instead of positional hash \\u2014 crashes on multi-turn. ~$16/run (15x Claude). Polished architecture but wrong API calling convention.\"\n    },\n    {\n      \"slug\": \"gpt_5_5_codex\",\n      \"id\": \"gpt-5.5\",\n      \"label\": \"GPT 5.5 xHigh (Codex)\",\n      \"provider\": \"codex\",\n      \"runner_type\": \"codex\",\n      \"codex_reasoning_effort\": \"xhigh\",\n      \"selection_reason\": \"GPT 5.5 via Codex CLI at xhigh reasoning effort. Successor to GPT 5.4 \\u2014 matches gpt_5_4_codex config exactly so the comparison measures model capability delta, not harness differences. Expected to produce similar ~$16/run cost band.\"\n    },\n    {\n      \"slug\": \"gpt_5_6_sol\",\n      \"id\": \"gpt-5.6-sol\",\n      \"label\": \"GPT 5.6 Sol xHigh (Codex)\",\n      \"provider\": \"codex\",\n      \"runner_type\": \"codex\",\n      \"codex_reasoning_effort\": \"xhigh\",\n      \"selection_reason\": \"GPT 5.6 Sol via Codex CLI at xhigh reasoning effort, run 2026-07-10 on the user's ChatGPT subscription (codex logged in via ChatGPT; probe confirmed gpt-5.6-sol + xhigh accepted). OpenAI's new-generation flagship (Sol/Terra/Luna naming), public release delayed by a US government review; API rates $5/$30 per M (same card as GPT 5.5). Mirrors gpt_5_4_codex/gpt_5_5_codex config so the comparison measures model delta, not harness differences. A gpt-5.6-sol-pro variant also exists on OpenRouter (untested, likely the $30/$180-class tier).\"\n    },\n    {\n      \"slug\": \"sakana_fugu\",\n      \"id\": \"sakana/fugu\",\n      \"label\": \"Sakana Fugu\",\n      \"provider\": \"sakana\",\n      \"skip_by_default\": true,\n      \"opencode_model_options\": {\n        \"tool_call\": true,\n        \"limit\": {\n          \"context\": 1000000,\n          \"output\": 32768\n        }\n      },\n      \"selection_reason\": \"Sakana Fugu default router via Sakana's OpenAI-compatible Chat Completions API (https://api.sakana.ai/v1). Docs list 1M context, streaming, tools/tool_choice, and reasoning effort high/xhigh/max; this opencode path uses @ai-sdk/openai-compatible with SAKANA_AI_TOKEN because the benchmark harness expects Chat Completions-style tool calling. Skipped by default until an in-house benchmark run confirms cost, latency, and long-session stability.\"\n    },\n    {\n      \"slug\": \"sakana_fugu_ultra\",\n      \"id\": \"sakana/fugu-ultra\",\n      \"label\": \"Sakana Fugu Ultra\",\n      \"provider\": \"sakana\",\n      \"skip_by_default\": true,\n      \"opencode_model_options\": {\n        \"tool_call\": true,\n        \"limit\": {\n          \"context\": 1000000,\n          \"output\": 32768\n        }\n      },\n      \"selection_reason\": \"Sakana Fugu Ultra via Sakana's OpenAI-compatible Chat Completions API. Docs describe it as the higher-quality/deeper multi-agent Fugu mode with 1M context, tools/tool_choice, streaming, and fixed pay-as-you-go pricing for fugu-ultra-20260615 ($5/M input, $30/M output; higher above 272K context). Skipped by default because long benchmark sessions may be slower/costlier and should be launched explicitly.\"\n    },\n    {\n      \"slug\": \"gpt_5_4_multi_balanced\",\n      \"id\": \"gpt-5.4\",\n      \"label\": \"GPT 5.4 xHigh + medium coder (Codex multi-agent)\",\n      \"provider\": \"codex\",\n      \"runner_type\": \"codex\",\n      \"codex_reasoning_effort\": \"xhigh\",\n      \"skip_by_default\": true,\n      \"codex_subagent\": {\n        \"name\": \"coder\",\n        \"model\": \"gpt-5.4\",\n        \"reasoning_effort\": \"medium\",\n        \"description\": \"Use proactively for concrete coding execution: file edits, refactors, bug fixes, test writing, boilerplate generation. The main session (xhigh) plans and delegates; this agent (medium) executes. Skip delegation for cross-file architectural decisions or complex root-cause debugging.\",\n        \"prompt\": \"You are a focused coding agent. The parent (xhigh) has already decided the approach \\u2014 your job is to execute cleanly. Follow instructions precisely. Don't re-plan or second-guess. Match existing codebase style. Keep changes minimal \\u2014 do what was asked, nothing more. Default to no comments. Run tests after significant edits if the tooling is obvious.\"\n      },\n      \"selection_reason\": \"Codex multi-agent: xhigh plans and orchestrates, medium/balanced handles coding. Tests whether GPT 5.4 at lower effort can execute well when the xhigh parent makes decisions. Comparison against gpt_5_4_codex (xhigh alone).\"\n    },\n    {\n      \"slug\": \"gpt_5_4_multi_balanced_forced\",\n      \"id\": \"gpt-5.4\",\n      \"label\": \"GPT 5.4 xHigh + medium coder (FORCED delegation)\",\n      \"provider\": \"codex\",\n      \"runner_type\": \"codex\",\n      \"codex_reasoning_effort\": \"xhigh\",\n      \"skip_by_default\": true,\n      \"codex_subagent\": {\n        \"name\": \"coder\",\n        \"model\": \"gpt-5.4\",\n        \"reasoning_effort\": \"medium\",\n        \"description\": \"Use for all concrete coding execution dispatched by the planner-orchestrator.\",\n        \"prompt\": \"You are a focused coding agent. Execute the dispatched subtask exactly as specified. Follow the provided instructions, file paths, and acceptance criteria literally. If the subtask is ambiguous, pick the most reasonable interpretation and note it in your reply. Keep changes minimal \\u2014 only do what the subtask describes. Match existing codebase style.\"\n      },\n      \"selection_reason\": \"Forced-delegation variant of gpt_5_4_multi_balanced. Same config as the free-choice version \\u2014 the only difference is the forcing prompt at prompts/benchmark_prompt_forced_delegation.txt. Measures whether forcing the orchestrator pattern changes output quality or cost on Codex's multi_agent feature.\"\n    },\n    {\n      \"slug\": \"gpt_5_4_multi_faster_forced\",\n      \"id\": \"gpt-5.4\",\n      \"label\": \"GPT 5.4 xHigh + low coder (FORCED delegation)\",\n      \"provider\": \"codex\",\n      \"runner_type\": \"codex\",\n      \"codex_reasoning_effort\": \"xhigh\",\n      \"skip_by_default\": true,\n      \"codex_subagent\": {\n        \"name\": \"coder\",\n        \"model\": \"gpt-5.4\",\n        \"reasoning_effort\": \"low\",\n        \"description\": \"Use for all concrete coding execution dispatched by the planner-orchestrator.\",\n        \"prompt\": \"You are a fast coding agent. Execute the dispatched subtask exactly as specified. Follow instructions literally. Keep changes minimal.\"\n      },\n      \"selection_reason\": \"Forced-delegation variant of gpt_5_4_multi_faster. Compares against the free-choice version to isolate the effect of the forcing prompt.\"\n    },\n    {\n      \"slug\": \"gpt_5_4_multi_faster\",\n      \"id\": \"gpt-5.4\",\n      \"label\": \"GPT 5.4 xHigh + low coder (Codex multi-agent)\",\n      \"provider\": \"codex\",\n      \"runner_type\": \"codex\",\n      \"codex_reasoning_effort\": \"xhigh\",\n      \"skip_by_default\": true,\n      \"codex_subagent\": {\n        \"name\": \"coder\",\n        \"model\": \"gpt-5.4\",\n        \"reasoning_effort\": \"low\",\n        \"description\": \"Use proactively for simple, high-volume coding execution: file edits, boilerplate generation, test scaffolding, single-file implementations. The main session (xhigh) plans; this agent (low) executes as cheaply as possible. Skip delegation for anything requiring judgment.\",\n        \"prompt\": \"You are a fast coding agent. The parent has already decided what to do \\u2014 just execute. Follow instructions literally. Keep changes minimal. No comments unless asked.\"\n      },\n      \"selection_reason\": \"Codex multi-agent: xhigh plans, low handles fast coding. Tests the 'cheap executor' hypothesis \\u2014 whether minimal reasoning on the subagent is enough when the parent provides the plan.\"\n    },\n    {\n      \"slug\": \"kimi_k2_5\",\n      \"id\": \"openrouter/moonshotai/kimi-k2.5\",\n      \"label\": \"Kimi K2.5\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"Chosen as the latest/highest Kimi variant listed by OpenRouter locally.\"\n    },\n    {\n      \"slug\": \"kimi_k2_6\",\n      \"id\": \"openrouter/moonshotai/kimi-k2.6\",\n      \"label\": \"Kimi K2.6\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"Direct successor to K2.5. $0.74/$4.66 per M, 256K context, tool calling supported. Tests whether K2.6 fixes K2.5's Tier 3 hallucinations of RubyLLM add_message() and complete().\"\n    },\n    {\n      \"slug\": \"kimi_k2_7_code\",\n      \"id\": \"openrouter/moonshotai/kimi-k2.7-code\",\n      \"label\": \"Kimi K2.7 Code\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"MoonshotAI Kimi K2.7 Code on OpenRouter. Direct successor to K2.6 for coding. OpenRouter lists 262K context, tool calling, structured outputs, and reasoning controls; pricing $0.95/M input and $4/M output. Tests whether the Kimi line keeps K2.6's Tier A trajectory while improving RubyLLM API accuracy and Rails app execution quality.\"\n    },\n    {\n      \"slug\": \"kimi_k3\",\n      \"id\": \"openrouter/moonshotai/kimi-k3\",\n      \"label\": \"Kimi K3\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"Moonshot Kimi K3 on OpenRouter ($3/$15, 1M ctx, reasoning). HARNESS-INCOMPATIBLE with opencode as of 2026-07-16: K3's Moonshot endpoint enforces strict JSON-schema validation and rejects opencode's tool definitions ('when using anyOf, type should be defined in anyOf items instead of the parent schema'). Controlled probe confirmed K3 tool-calling works with clean schemas \\u2014 the model is fine, the opencode toolset pairing is broken (same genre as DeepSeek V4 Pro reasoning_content). Only upstream is Moonshot itself (no alternate OR provider to route around). Retest when opencode normalizes tool schemas or another provider serves K3. K2.5/K2.6/K2.7 ran fine with identical tooling.\",\n      \"skip_by_default\": true\n    },\n    {\n      \"slug\": \"kimi_k3_cli\",\n      \"id\": \"kimi-code/k3\",\n      \"label\": \"Kimi K3 (Kimi Code CLI)\",\n      \"provider\": \"kimi\",\n      \"runner_type\": \"kimi\",\n      \"selection_reason\": \"Kimi K3 via Moonshot's own Kimi Code CLI (runner_type kimi, added 2026-07-16), billed via Kimi subscription OAuth. Workaround for the opencode incompatibility (Moonshot rejects opencode's anyOf tool schemas) \\u2014 same precedent as GPT 5.4 via Codex CLI. 256K context on this plan. Non-interactive via -p + --output-format stream-json; phase 2 via -S <session>; tokens from kimi export wire.jsonl step.end sums.\"\n    },\n    {\n      \"slug\": \"kimi_k2_7_coding_cli\",\n      \"id\": \"kimi-code/kimi-for-coding\",\n      \"label\": \"Kimi K2.7 Coding (Kimi Code CLI)\",\n      \"provider\": \"kimi\",\n      \"runner_type\": \"kimi\",\n      \"skip_by_default\": true,\n      \"selection_reason\": \"K2.7 Coding via Kimi Code CLI \\u2014 HARNESS-COMPARISON run against the opencode kimi_k2_7_code result (86/A). Managed 'kimi-for-coding' model; Moonshot positions it as the K2.7 Code lineage though the serving snapshot may differ from OpenRouter's kimi-k2.7-code. skip_by_default: comparison study only, not part of the default set. Note: the Kimi subscription does NOT expose K2.5/K2.6, so the harness comparison is limited to the K2.7 generation.\"\n    },\n    {\n      \"slug\": \"grok_4_3\",\n      \"id\": \"openrouter/x-ai/grok-4.3\",\n      \"label\": \"Grok 4.3\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"x.AI Grok 4.3 via OpenRouter. $1.25/$2.50 per M (mid-tier), 1M context, tool calling supported. First Grok variant in the benchmark \\u2014 tests whether Grok's RubyLLM API recall is correct (real chat.ask path) or hits the same fluent-DSL/chat.complete hallucinations seen in some Tier B/C cloud models. Pricing positions it between Kimi K2.6 ($0.50/$2.50) and DeepSeek V4 Pro ($0.44/$0.87), well below Opus ($5/$25).\"\n    },\n    {\n      \"slug\": \"grok_4_5\",\n      \"id\": \"openrouter/x-ai/grok-4.5\",\n      \"label\": \"Grok 4.5\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"xAI Grok 4.5 via OpenRouter (snapshot grok-4.5-20260708, released 2026-07-08). xAI's flagship 'smartest model' with frontier coding claims. 500K context, $2/$6 per M, tool calling + reasoning supported. Reasoning effort maxes at 'high' which is the DEFAULT (no xhigh tier; reasoning cannot be disabled), so the standard run is already highest-effort. Tests whether 4.5 fixes the Grok-family weaknesses: 4.20's Tier D collapse and 4.3's dead Stimulus wiring, bypassed test stubs, and stale claude-3.7-sonnet pin.\"\n    },\n    {\n      \"slug\": \"mimo_v2_5_pro\",\n      \"id\": \"openrouter/xiaomi/mimo-v2.5-pro\",\n      \"label\": \"Xiaomi MiMo V2.5 Pro\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"Xiaomi's flagship coding model. $1/$3 per M, 1M context, tool calling supported. Brand-new family we haven't tested \\u2014 competitive pricing with mid-tier Chinese models like Kimi and GLM.\"\n    },\n    {\n      \"slug\": \"glm_5\",\n      \"id\": \"openrouter/z-ai/glm-5\",\n      \"label\": \"GLM 5\",\n      \"provider\": \"openrouter\",\n      \"skip_by_default\": true,\n      \"selection_reason\": \"Chosen as the latest/highest GLM variant listed by OpenRouter locally; this replaces the local GLM test. Skipped by default because it completed with errors in the previous benchmark pass.\"\n    },\n    {\n      \"slug\": \"qwen3_6_plus\",\n      \"id\": \"openrouter/qwen/qwen3.6-plus\",\n      \"label\": \"Qwen 3.6 Plus\",\n      \"provider\": \"openrouter\",\n      \"skip_by_default\": true,\n      \"selection_reason\": \"Added from OpenRouter cloud availability; chose the non-preview Qwen 3.6 Plus variant exposed locally. Skipped by default because it completed with errors in the previous benchmark pass.\"\n    },\n    {\n      \"slug\": \"qwen3_5_397b_cloud\",\n      \"id\": \"openrouter/qwen/qwen3.5-397b-a17b\",\n      \"label\": \"Qwen 3.5 397B Cloud\",\n      \"provider\": \"openrouter\",\n      \"skip_by_default\": true,\n      \"selection_reason\": \"The raw OpenRouter Qwen 3.5 397B A17B base \\u2014 the architecture Nex AGI fine-tuned into Nex-N2-Pro. Force-run 2026-06-15 as a controlled base-vs-fine-tune comparison: completed_with_errors at 42/100 Tier C (hallucinates the RubyLLM API via chat.system/chat.user/response.text, builds in a nested chat-app/ subdir, tests mock the hallucinated API). Kept skip_by_default because it's a broken Tier C reference run, not a routine target. See Cross-Cutting Finding #6 in docs/success_report.md.\"\n    },\n    {\n      \"slug\": \"gemma4_31b_cloud\",\n      \"id\": \"openrouter/google/gemma-4-31b-it\",\n      \"label\": \"Gemma 4 31B Cloud\",\n      \"provider\": \"openrouter\",\n      \"skip_by_default\": true,\n      \"selection_reason\": \"Google Gemma 4 31B IT BF16 served via Ollama's hosted cloud (https://ollama.com). Originally added to bypass the local llama.cpp parser bugs that caused infinite repetition loops on local Q3/Q8 GGUFs. Curl tests confirm the model itself works correctly for tool calling. **However, opencode benchmark runs hit HTTP 504 Gateway Timeout consistently around 20-24K total tokens of conversation history** \\u2014 Cloudflare edge appears to enforce a ~100s per-request limit which 20K+ token prefill exceeds. Tried maxRetries:5 (didn't help \\u2014 failures are consistent, not transient). Set limit.context:16384 to force opencode history trimming below the wall. Skipped by default until either Ollama Cloud raises the timeout or we test via Google's native Gemini API. Requires OLLAMA_API_KEY env var with Ollama Cloud subscription.\"\n    },\n    {\n      \"slug\": \"llama4_scout_cloud\",\n      \"id\": \"openrouter/meta-llama/llama-4-scout\",\n      \"label\": \"Llama 4 Scout Cloud\",\n      \"provider\": \"openrouter\",\n      \"skip_by_default\": true,\n      \"selection_reason\": \"Added as the OpenRouter cloud Llama 4 Scout benchmark counterpart to the unusable local Scout path. Skipped by default because it does not currently resolve cleanly in this opencode build.\"\n    },\n    {\n      \"slug\": \"nemotron_3_super_cloud\",\n      \"id\": \"openrouter/nvidia/nemotron-3-super-120b-a12b\",\n      \"label\": \"Nemotron 3 Super Cloud\",\n      \"provider\": \"openrouter\",\n      \"skip_by_default\": true,\n      \"selection_reason\": \"Added as the closest OpenRouter cloud Nemotron line available after local Nemotron Cascade 2 proved unusable in this harness. Skipped by default because it still needs a clean first benchmark run.\"\n    },\n    {\n      \"slug\": \"minimax_m2_7\",\n      \"id\": \"openrouter/minimax/minimax-m2.7\",\n      \"label\": \"MiniMax M2.7\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"Chosen as the largest/latest MiniMax variant listed by OpenRouter locally.\"\n    },\n    {\n      \"slug\": \"minimax_m3\",\n      \"id\": \"openrouter/minimax/minimax-m3\",\n      \"label\": \"MiniMax M3\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"MiniMax M3 on OpenRouter. Direct successor to MiniMax M2.7. 1M context, tool calling supported, $0.30/M input and $1.20/M output. Tests whether the new MiniMax release fixes M2.7's RubyLLM batch-form hallucination and becomes a viable low-cost Rails/RubyLLM builder. Cloud-only: a GGUF exists (unsloth/MiniMax-M3-GGUF, ollama.com/library/minimax-m3), but as a 230B-total MoE it needs ~195 GB (Q3) / ~264 GB (Q4) for weights alone; usable inference also needs KV cache, runtime scratch, and OS headroom, so it exceeds both local profiles (RTX 5090 32 GB; Strix Halo \\u2264128 GB) \\u2014 see docs/llama-swap.md.\"\n    },\n    {\n      \"slug\": \"deepseek_v3_2\",\n      \"id\": \"openrouter/deepseek/deepseek-v3.2\",\n      \"label\": \"DeepSeek V3.2\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"Latest DeepSeek model on OpenRouter. Input $0.26/M, output $0.38/M.\"\n    },\n    {\n      \"slug\": \"deepseek_v4_flash\",\n      \"id\": \"openrouter/deepseek/deepseek-v4-flash\",\n      \"label\": \"DeepSeek V4 Flash\",\n      \"provider\": \"openrouter\",\n      \"enable_followup\": false,\n      \"selection_reason\": \"DeepSeek V4 Flash \\u2014 budget-tier variant at $0.14/M input, $0.28/M output (cheaper than V3.2). 1M context. Tool calling supported via OpenRouter. Test whether V4 fixes the RubyLLM API hallucination that made V3.2 Tier 3. Phase 2 disabled: DeepSeek's thinking-mode API rejects replayed `reasoning_content` tokens from opencode's session continuation.\"\n    },\n    {\n      \"slug\": \"deepseek_v4_pro\",\n      \"id\": \"openrouter/deepseek/deepseek-v4-pro\",\n      \"label\": \"DeepSeek V4 Pro\",\n      \"provider\": \"openrouter\",\n      \"enable_followup\": false,\n      \"opencode_model_options\": {\n        \"reasoning\": false\n      },\n      \"selection_reason\": \"DeepSeek V4 Pro \\u2014 premium variant at $1.74/M input, $3.48/M output. 1M context. Uses thinking mode by default which requires the client to echo reasoning_content on subsequent turns (opencode doesn't). reasoning=false tells opencode to treat it as a non-reasoning model so it won't extract/pass back reasoning_content.\"\n    },\n    {\n      \"slug\": \"step_3_5_flash\",\n      \"id\": \"openrouter/stepfun/step-3.5-flash\",\n      \"label\": \"Step 3.5 Flash\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"StepFun Step 3.5 Flash on OpenRouter. Input $0.10/M, output $0.30/M.\"\n    },\n    {\n      \"slug\": \"step_3_7_flash\",\n      \"id\": \"openrouter/stepfun/step-3.7-flash\",\n      \"label\": \"Step 3.7 Flash\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"StepFun Step 3.7 Flash on OpenRouter (snapshot step-3.7-flash-20260528). Added 2026-06-15 per community Issue #7. 256K context, tool calling supported, $0.20/M input and $1.15/M output. Tests whether 3.7 fixes Step 3.5's ruby-openai bypass (3.5 scored 56/C \\u26a0\\ufe0f bypass for using the wrong gem instead of ruby_llm).\"\n    },\n    {\n      \"slug\": \"claude_sonnet_4_6\",\n      \"id\": \"openrouter/anthropic/claude-sonnet-4.6\",\n      \"label\": \"Claude Sonnet 4.6\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"Anthropic Claude Sonnet 4.6 on OpenRouter. Input $3.00/M, output $15.00/M.\"\n    },\n    {\n      \"slug\": \"gemini_3_1_pro\",\n      \"id\": \"openrouter/google/gemini-3.1-pro-preview\",\n      \"label\": \"Gemini 3.1 Pro\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"Latest Google Gemini model with enhanced SWE performance and agentic reliability. Input $2.00/M, output $12.00/M.\"\n    },\n    {\n      \"slug\": \"gemini_3_5_flash\",\n      \"id\": \"openrouter/google/gemini-3.5-flash\",\n      \"label\": \"Gemini 3.5 Flash\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"Google Gemini 3.5 Flash on OpenRouter (GA snapshot gemini-3.5-flash-20260519). Added 2026-06-15 to run + score in-house after community PR #6 submitted pre-scored results without the gitignored project code. Input $1.50/M, output $9.00/M, 1M context. Tests whether a Flash-tier model can match the 3.1 Pro RubyLLM correctness baseline.\"\n    },\n    {\n      \"slug\": \"grok_4_20\",\n      \"id\": \"openrouter/x-ai/grok-4.20\",\n      \"label\": \"Grok 4.20\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"xAI's latest flagship on OpenRouter. Fastest model in the benchmark (8 min) but produced architecturally broken code: bypassed RubyLLM with ruby-openai (only in dev/test group, NameError in prod), used format.turbo_stream without installing turbo-rails, RUBY_VERSION=4.0.2 Dockerfile bug. Tier 3 \\u2014 broken core.\"\n    },\n    {\n      \"slug\": \"glm_5_1\",\n      \"id\": \"zai/glm-5.1\",\n      \"label\": \"GLM 5.1\",\n      \"provider\": \"zai\",\n      \"selection_reason\": \"Z.ai's latest flagship GLM model. Uses Z.ai coding plan endpoint at https://api.z.ai/api/coding/paas/v4 (NOT the general /api/paas/v4) \\u2014 Lite subscription includes glm-5.1 only via the coding endpoint. Completed in 22 min with 24 tests, correct primary RubyLLM.chat/ask usage, but invented chat.user/chat.assistant for multi-turn history seeding (single-turn works, multi-turn crashes). Tier 2 \\u2014 works with caveats.\"\n    },\n    {\n      \"slug\": \"glm_5_2\",\n      \"id\": \"zai/glm-5.2\",\n      \"label\": \"GLM 5.2\",\n      \"provider\": \"zai\",\n      \"selection_reason\": \"Z.ai's newest flagship GLM (released 2026-06). Served on the coding plan endpoint at https://api.z.ai/api/coding/paas/v4 (live and key-verified 2026-06-14, though not yet in that endpoint's /models listing; not on OpenRouter yet). Like all GLM models it returns reasoning in reasoning_content with empty content by default \\u2014 the zai provider wiring already handles this for GLM 5.1. Tests whether 5.2 fixes 5.1's hallucinated chat.user/chat.assistant multi-turn DSL (the bug that put 5.1 in Tier C).\"\n    },\n    {\n      \"slug\": \"qwen3_5_27b_claude\",\n      \"id\": \"ollama/qwen/qwen3.5-27b-claude\",\n      \"label\": \"Qwen 3.5 27B Claude Distilled\",\n      \"provider\": \"ollama\",\n      \"llama_swap_model\": \"qwen3.5:27b-claude\",\n      \"selection_reason\": \"Qwen 3.5 27B distilled from Claude 4.6 Opus reasoning traces (Jackrong/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled). Tests whether Claude reasoning distillation transfers RubyLLM API correctness \\u2014 most non-Anthropic models hallucinate the gem's API, so a Claude-distilled Qwen is an interesting natural experiment.\"\n    },\n    {\n      \"slug\": \"qwen2_5_coder_32b\",\n      \"id\": \"ollama/qwen/qwen2.5-coder-32b\",\n      \"label\": \"Qwen 2.5 Coder 32B\",\n      \"provider\": \"ollama\",\n      \"skip_by_default\": true,\n      \"llama_swap_model\": \"qwen2.5-coder:32b\",\n      \"selection_reason\": \"Most popular dedicated coder of the Qwen 2.5 generation. Sourced from Ollama (Q4_K_M ~19 GB). On NVIDIA 5090 fits with 64K context.\"\n    },\n    {\n      \"slug\": \"qwen3_coder_30b\",\n      \"id\": \"ollama/qwen/qwen3-coder-30b\",\n      \"label\": \"Qwen 3 Coder 30B\",\n      \"provider\": \"ollama\",\n      \"skip_by_default\": true,\n      \"llama_swap_model\": \"qwen3-coder:30b\",\n      \"selection_reason\": \"Qwen 3 dedicated coder variant (the regular 30B, not the 51 GB qwen3-coder-next-ctx). Direct comparison with the general qwen3:32b. Sourced from Ollama (Q4_K_M ~18 GB).\"\n    },\n    {\n      \"slug\": \"qwen3_5_27b_sushi_coder\",\n      \"id\": \"ollama/qwen/qwen3.5-27b-sushi-coder\",\n      \"label\": \"Qwen 3.5 27B Sushi Coder RL\",\n      \"provider\": \"ollama\",\n      \"skip_by_default\": true,\n      \"llama_swap_model\": \"qwen3.5-sushi-coder:27b\",\n      \"selection_reason\": \"Qwen 3.5 27B fine-tuned via reinforcement learning on Codeforces problems (bigatuna/Qwen3.5-27b-Sushi-Coder-RL). Q4_K_M ~15 GB. Tests whether RL coding fine-tuning transfers correct RubyLLM API usage \\u2014 direct comparison with the Claude reasoning distillation (qwen3.5:27b-claude) and the general qwen3.5:35b.\"\n    },\n    {\n      \"slug\": \"gemma4_31b_cloud\",\n      \"id\": \"ollama-cloud/gemma4-31b\",\n      \"label\": \"Gemma 4 31B (Ollama Cloud)\",\n      \"provider\": \"ollama-cloud\",\n      \"selection_reason\": \"Google Gemma 4 31B IT BF16 served via Ollama's hosted cloud (https://ollama.com). Bypasses the local llama.cpp parser bugs that caused infinite repetition loops on local Q3/Q8 GGUFs. Tests whether Gemma 4 is actually capable for agentic tool calling when served by Google's full-precision infrastructure rather than crippled by quantization + parser regressions. Requires OLLAMA_API_KEY env var with an Ollama Cloud subscription.\"\n    },\n    {\n      \"slug\": \"qwen3_7_max\",\n      \"id\": \"openrouter/qwen/qwen3.7-max\",\n      \"label\": \"Qwen3.7 Max\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"Alibaba Qwen3.7 Max on OpenRouter. Added 2026-06-15 to run + score in-house after community PR #4 submitted pre-scored results (82/A on a phase-2 DNF) without the gitignored project code. Tests whether the flagship Qwen Max tier achieves correct RubyLLM API usage and completes phase 2 validation under our harness.\"\n    },\n    {\n      \"slug\": \"nex_n2_pro\",\n      \"id\": \"openrouter/nex-agi/nex-n2-pro:free\",\n      \"label\": \"Nex-N2-Pro\",\n      \"provider\": \"openrouter\",\n      \"selection_reason\": \"Nex AGI Nex-N2-Pro on OpenRouter (free tier). Agentic MoE, 397B total / 17B active, built on the Qwen3.5-397B-A17B architecture with 'Adaptive Thinking'; 262K context, supports tool calling. Added 2026-06-15. Vendor claims rival GPT-5.5/Opus 4.7 on coding (SWE-Bench Verified ~80.8). Tests whether Nex AGI's agentic fine-tune of the Qwen3.5 base fixes the RubyLLM API hallucination that the Qwen3.5 family typically exhibits. Caveat: the :free endpoint has aggressive rate limits that may stall a long agentic run.\"\n    }\n  ]\n}"}}, "results/mimo_v2_5_pro/phase2-result.json": {"4ad84ee9510a59ddd101e621b23d6210358994b7": {"t": 1785674310.8320808, "n": 4402, "h": "82512a566b76dab5", "c": "{\n  \"assistant_output_excerpt\": \"The production environment requires `SECRET_KEY_BASE`. Let me fix the docker-compose.yml and also set up credentials properly.\\nAll validation complete. Summary:\\n\\n| Step | Result |\\n|---|---|\\n| **Local boot** | Puma starts, HTTP 200, correct HTML with Tailwind + Hotwire |\\n| **Tests** | 21 pass, 39 assertions, 85% coverage |\\n| **`docker build`** | Builds successfully (cached layers, assets precompiled) |\\n| **`docker compose up --build`** | Container runs, Puma listens on :3000, HTTP 200 |\\n\\n**Fixes applied in this phase:**\\n- Added `SECRET_KEY_BASE` to `docker-compose.yml` environment (required for production Rails)\\n- Updated README Docker instructions to use a `.env` file for secrets\\n- Removed `RAILS_MASTER_KEY` from docker-compose (not needed without encrypted credentials)\",\n  \"command\": [\n    \"opencode\",\n    \"run\",\n    \"--agent\",\n    \"build\",\n    \"--format\",\n    \"json\",\n    \"--session\",\n    \"ses_23fdc9eceffeHMOxZ1mCxH0PdG\",\n    \"Once finished coding and testing, you must make sure it runs, both locally, and that docker build also finishes successfully, and docker compose is able to run.\\n\\nDo not ask for confirmation. Do not stop with a plan. Fulfill the request and finish.\\n\\nThis is phase 2 of 2 and a continuation of the existing project in the current working directory. Do not regenerate the app. Do not create a second app. Validate and fix the current codebase in place.\\n\\nUse environment variables so RubyLLM actually works. Source ~/.config/zsh/secrets only to load the required environment, especially OPENROUTER_API_KEY. Do not print secret values, do not copy secret file contents into the repo, and do not commit secrets into files, logs, Dockerfiles, compose files, or README examples.\\n\\nValidate the project end-to-end in this order:\\n- run the local app in a way that proves it boots\\n- make any fixes needed so it boots cleanly\\n- make sure `docker build` finishes successfully\\n- make sure `docker compose up --build` is able to run\\n\\nIf one step passes, move to the next without asking for confirmation. If something fails, fix it and continue. Only stop when you have actually completed the validation work or you hit a hard blocker you cannot resolve from inside the workspace.\"\n  ],\n  \"continued_from_session\": \"ses_23fdc9eceffeHMOxZ1mCxH0PdG\",\n  \"elapsed_seconds\": 279.29,\n  \"ended_at\": \"2026-04-24T15:48:00+00:00\",\n  \"exit_code\": 0,\n  \"finish_reason\": \"stop\",\n  \"model\": {\n    \"id\": \"openrouter/xiaomi/mimo-v2.5-pro\",\n    \"label\": \"Xiaomi MiMo V2.5 Pro\",\n    \"provider\": \"openrouter\",\n    \"selection_reason\": \"Xiaomi's flagship coding model. $1/$3 per M, 1M context, tool calling supported. Brand-new family we haven't tested \\u2014 competitive pricing with mid-tier Chinese models like Kimi and GLM.\",\n    \"slug\": \"mimo_v2_5_pro\"\n  },\n  \"no_progress_timeout_seconds\": 360,\n  \"opencode_session_id\": \"ses_23fdc9eceffeHMOxZ1mCxH0PdG\",\n  \"output_tokens_per_second\": 0.63,\n  \"paths\": {\n    \"opencode_config\": \"config/opencode.benchmark.json\",\n    \"project_dir\": \"results/mimo_v2_5_pro/project\",\n    \"prompt\": \"results/mimo_v2_5_pro/followup-prompt.txt\",\n    \"stderr\": \"results/mimo_v2_5_pro/followup-opencode-stderr.log\",\n    \"stdout\": \"results/mimo_v2_5_pro/followup-opencode-output.ndjson\"\n  },\n  \"phase\": \"phase2\",\n  \"preview_output_tokens_per_second\": 68.74,\n  \"preview_output_tokens_per_second_average\": 51.05,\n  \"project_summary\": {\n    \"file_count\": 1554,\n    \"present\": {\n      \"app_dir\": true,\n      \"compose_yaml\": false,\n      \"compose_yml\": false,\n      \"docker_compose_yaml\": false,\n      \"docker_compose_yml\": true,\n      \"dockerfile\": true,\n      \"gemfile\": true,\n      \"javascript_dir\": true,\n      \"readme_lower\": false,\n      \"readme_md\": true,\n      \"routes\": true,\n      \"tests_dir\": true,\n      \"views_dir\": true\n    },\n    \"works_as_intended\": \"yes\",\n    \"works_note\": \"Rails app, tests, README, and container files detected.\"\n  },\n  \"prompt_sha256\": \"e2f60835f36832ba1242d6f23a02bd7958611c52f2db122a3df93f8727dab9b5\",\n  \"stall_reason\": null,\n  \"stalled\": false,\n  \"started_at\": \"2026-04-24T15:43:21+00:00\",\n  \"status\": \"completed\",\n  \"stderr_excerpt\": \"\",\n  \"timed_out\": false,\n  \"timeout_seconds\": 5400,\n  \"tokens\": {\n    \"cache\": {\n      \"read\": 79936,\n      \"write\": 0\n    },\n    \"input\": 323,\n    \"output\": 177,\n    \"reasoning\": 11,\n    \"total\": 80447\n  },\n  \"tokens_per_second\": 288.04\n}\n"}}, "results/mimo_v2_5_pro/result.json": {"4ad84ee9510a59ddd101e621b23d6210358994b7": {"t": 1785674310.8356395, "n": 15856, "h": "241ea36a9539a9d8", "c": "{\n  \"assistant_output_excerpt\": \"The production environment requires `SECRET_KEY_BASE`. Let me fix the docker-compose.yml and also set up credentials properly.\\nAll validation complete. Summary:\\n\\n| Step | Result |\\n|---|---|\\n| **Local boot** | Puma starts, HTTP 200, correct HTML with Tailwind + Hotwire |\\n| **Tests** | 21 pass, 39 assertions, 85% coverage |\\n| **`docker build`** | Builds successfully (cached layers, assets precompiled) |\\n| **`docker compose up --build`** | Container runs, Puma listens on :3000, HTTP 200 |\\n\\n**Fixes applied in this phase:**\\n- Added `SECRET_KEY_BASE` to `docker-compose.yml` environment (required for production Rails)\\n- Updated README Docker instructions to use a `.env` file for secrets\\n- Removed `RAILS_MASTER_KEY` from docker-compose (not needed without encrypted credentials)\",\n  \"command\": [\n    \"opencode\",\n    \"run\",\n    \"--agent\",\n    \"build\",\n    \"--format\",\n    \"json\",\n    \"--session\",\n    \"ses_23fdc9eceffeHMOxZ1mCxH0PdG\",\n    \"Once finished coding and testing, you must make sure it runs, both locally, and that docker build also finishes successfully, and docker compose is able to run.\\n\\nDo not ask for confirmation. Do not stop with a plan. Fulfill the request and finish.\\n\\nThis is phase 2 of 2 and a continuation of the existing project in the current working directory. Do not regenerate the app. Do not create a second app. Validate and fix the current codebase in place.\\n\\nUse environment variables so RubyLLM actually works. Source ~/.config/zsh/secrets only to load the required environment, especially OPENROUTER_API_KEY. Do not print secret values, do not copy secret file contents into the repo, and do not commit secrets into files, logs, Dockerfiles, compose files, or README examples.\\n\\nValidate the project end-to-end in this order:\\n- run the local app in a way that proves it boots\\n- make any fixes needed so it boots cleanly\\n- make sure `docker build` finishes successfully\\n- make sure `docker compose up --build` is able to run\\n\\nIf one step passes, move to the next without asking for confirmation. If something fails, fix it and continue. Only stop when you have actually completed the validation work or you hit a hard blocker you cannot resolve from inside the workspace.\"\n  ],\n  \"continued_from_session\": \"ses_23fdc9eceffeHMOxZ1mCxH0PdG\",\n  \"elapsed_seconds\": 644.4,\n  \"ended_at\": \"2026-04-24T15:48:01+00:00\",\n  \"exit_code\": 0,\n  \"finish_reason\": \"stop\",\n  \"followup_prompt_sha256\": \"e2f60835f36832ba1242d6f23a02bd7958611c52f2db122a3df93f8727dab9b5\",\n  \"model\": {\n    \"id\": \"openrouter/xiaomi/mimo-v2.5-pro\",\n    \"label\": \"Xiaomi MiMo V2.5 Pro\",\n    \"provider\": \"openrouter\",\n    \"selection_reason\": \"Xiaomi's flagship coding model. $1/$3 per M, 1M context, tool calling supported. Brand-new family we haven't tested \\u2014 competitive pricing with mid-tier Chinese models like Kimi and GLM.\",\n    \"slug\": \"mimo_v2_5_pro\"\n  },\n  \"no_progress_timeout_seconds\": 360,\n  \"opencode_session_id\": \"ses_23fdc9eceffeHMOxZ1mCxH0PdG\",\n  \"output_tokens_per_second\": 0.63,\n  \"paths\": {\n    \"followup_prompt\": \"results/mimo_v2_5_pro/followup-prompt.txt\",\n    \"followup_stderr\": \"results/mimo_v2_5_pro/followup-opencode-stderr.log\",\n    \"followup_stdout\": \"results/mimo_v2_5_pro/followup-opencode-output.ndjson\",\n    \"opencode_config\": \"config/opencode.benchmark.json\",\n    \"project_dir\": \"results/mimo_v2_5_pro/project\",\n    \"prompt\": \"results/mimo_v2_5_pro/prompt.txt\",\n    \"session_export\": \"results/mimo_v2_5_pro/session-export.json\",\n    \"stderr\": \"results/mimo_v2_5_pro/opencode-stderr.log\",\n    \"stdout\": \"results/mimo_v2_5_pro/opencode-output.ndjson\"\n  },\n  \"phase\": \"phase2\",\n  \"phases\": [\n    {\n      \"assistant_output_excerpt\": \"Now I have a good understanding of the ruby_llm API. Let me create all the application files.\\nDone. Here's what was built:\\n\\n**RubyLLM Chat** \\u2014 a minimal ChatGPT-like SPA using Ruby 4.0.2, Rails 8.1.3, RubyLLM (OpenRouter + Claude Sonnet 4.6), Tailwind CSS, and Hotwire/Turbo Streams.\\n\\n### Key files\\n\\n| Component | File |\\n|---|---|\\n| RubyLLM config | `config/initializers/ruby_llm.rb` |\\n| Chat PORO | `app/models/chat_session.rb` |\\n| Thread-safe store | `app/models/chat_store.rb` |\\n| Controller | `app/controllers/chats_controller.rb`, `app/controllers/messages_controller.rb` |\\n| Views | `app/views/chats/show.html.erb`, `app/views/messages/_message.html.erb`, `app/views/messages/create.turbo_stream.erb` |\\n| Stimulus JS | `app/javascript/controllers/chat_form_controller.js`, `app/javascript/controllers/auto_resize_controller.js` |\\n| Tests | `test/models/`, `test/controllers/`, `test/helpers/` (21 tests, 39 assertions) |\\n| CI | `bin/ci` (RuboCop, Brakeman, bundle-audit, Minitest) |\\n| Docker | `Dockerfile`, `docker-compose.yml` |\\n\\n### Results\\n\\n- **21 tests passing**, 85% line coverage\\n- **RuboCop**: 0 offenses\\n- **Brakeman**: 0 warnings\\n- **bundle-audit**: no vulnerabilities found\",\n      \"command\": [\n        \"opencode\",\n        \"run\",\n        \"--agent\",\n        \"build\",\n        \"--format\",\n        \"json\",\n        \"-m\",\n        \"openrouter/xiaomi/mimo-v2.5-pro\",\n        \"I want you to build a Ruby on Rails application. Use the newest Ruby and Rails available in mise here; you have access to mise. First make a short implementation plan for yourself, then go ahead with the implementation without asking for confirmation. Do not stop to ask what to do next, do not answer with only a plan, and do not ask whether you should start creating files.\\n\\nUse only the tools available in this runtime. Do not call apply_patch. For file changes, use edit for existing files and write for new files. If a tool call fails, recover and continue implementing instead of stopping.\\n\\nUse the Rails generators to generate the initial code for the project. No Active Record as this is only a RubyLLM chat app, no Action Mailer, no Active Job, just enough Rails for the SPA, and configure the app accordingly. You will make a very simple SPA mimicking a minimal ChatGPT-like web interface. Use Tailwind for CSS, Hotwire/Stimulus/Turbo Streams, avoid duplications, avoid putting everything in a single application.css or application.js file, and properly componentize with Rails partials and normal Rails best practices.\\n\\nYou must use environment variables so RubyLLM actually works. Source ~/.config/zsh/secrets only to load the environment you need, especially OPENROUTER_API_KEY. Do not print secret values, do not copy secret file contents into the repo, and do not commit secrets into source files, .env files, Dockerfiles, compose files, logs, or README examples.\\n\\nUse the latest RubyLLM and configure it to connect to OpenRouter and use the latest Claude Sonnet for the chat. Add proper Minitest unit tests for each component. Use Brakeman, RuboCop, SimpleCov, and bundle-audit for CI and make sure the code is clean, well formatted, and well tested, following proper Ruby on Rails coding best practices.\\n\\nThis app will not have authentication. It is really a simple webpage for RubyLLM. Document the project in a README.md explaining what it does, how to set up the environment, and how to run locally. Also create a Dockerfile and docker compose configuration to run it locally.\\n\\nThis is phase 1 of 2. Focus on implementation, tests, and project structure. Do not spend time on full runtime validation beyond what is needed to keep implementation moving.\\n\\nStay inside the current workspace and modify the current project only. Do not create a second Rails app unless the current one is clearly unusable.\"\n      ],\n      \"continued_from_session\": null,\n      \"elapsed_seconds\": 365.11,\n      \"ended_at\": \"2026-04-24T15:43:21+00:00\",\n      \"exit_code\": 0,\n      \"finish_reason\": \"stop\",\n      \"model\": {\n        \"id\": \"openrouter/xiaomi/mimo-v2.5-pro\",\n        \"label\": \"Xiaomi MiMo V2.5 Pro\",\n        \"provider\": \"openrouter\",\n        \"selection_reason\": \"Xiaomi's flagship coding model. $1/$3 per M, 1M context, tool calling supported. Brand-new family we haven't tested \\u2014 competitive pricing with mid-tier Chinese models like Kimi and GLM.\",\n        \"slug\": \"mimo_v2_5_pro\"\n      },\n      \"no_progress_timeout_seconds\": 360,\n      \"opencode_session_id\": \"ses_23fdc9eceffeHMOxZ1mCxH0PdG\",\n      \"output_tokens_per_second\": 0.87,\n      \"paths\": {\n        \"opencode_config\": \"config/opencode.benchmark.json\",\n        \"project_dir\": \"results/mimo_v2_5_pro/project\",\n        \"prompt\": \"results/mimo_v2_5_pro/prompt.txt\",\n        \"stderr\": \"results/mimo_v2_5_pro/opencode-stderr.log\",\n        \"stdout\": \"results/mimo_v2_5_pro/opencode-output.ndjson\"\n      },\n      \"phase\": \"phase1\",\n      \"preview_output_tokens_per_second\": 73.83,\n      \"preview_output_tokens_per_second_average\": 38.84,\n      \"project_summary\": {\n        \"file_count\": 1372,\n        \"present\": {\n          \"app_dir\": true,\n          \"compose_yaml\": false,\n          \"compose_yml\": false,\n          \"docker_compose_yaml\": false,\n          \"docker_compose_yml\": true,\n          \"dockerfile\": true,\n          \"gemfile\": true,\n          \"javascript_dir\": true,\n          \"readme_lower\": false,\n          \"readme_md\": true,\n          \"routes\": true,\n          \"tests_dir\": true,\n          \"views_dir\": true\n        },\n        \"works_as_intended\": \"yes\",\n        \"works_note\": \"Rails app, tests, README, and container files detected.\"\n      },\n      \"prompt_sha256\": \"d25f119447215ebf47477c1ce61b24f801bfcb9336467f5b019d554f3c83537c\",\n      \"stall_reason\": null,\n      \"stalled\": false,\n      \"started_at\": \"2026-04-24T15:37:16+00:00\",\n      \"status\": \"completed\",\n      \"stderr_excerpt\": \"\",\n      \"timed_out\": false,\n      \"timeout_seconds\": 5400,\n      \"tokens\": {\n        \"cache\": {\n          \"read\": 56128,\n          \"write\": 0\n        },\n        \"input\": 607,\n        \"output\": 318,\n        \"reasoning\": 16,\n        \"total\": 57069\n      },\n      \"tokens_per_second\": 156.31\n    },\n    {\n      \"assistant_output_excerpt\": \"The production environment requires `SECRET_KEY_BASE`. Let me fix the docker-compose.yml and also set up credentials properly.\\nAll validation complete. Summary:\\n\\n| Step | Result |\\n|---|---|\\n| **Local boot** | Puma starts, HTTP 200, correct HTML with Tailwind + Hotwire |\\n| **Tests** | 21 pass, 39 assertions, 85% coverage |\\n| **`docker build`** | Builds successfully (cached layers, assets precompiled) |\\n| **`docker compose up --build`** | Container runs, Puma listens on :3000, HTTP 200 |\\n\\n**Fixes applied in this phase:**\\n- Added `SECRET_KEY_BASE` to `docker-compose.yml` environment (required for production Rails)\\n- Updated README Docker instructions to use a `.env` file for secrets\\n- Removed `RAILS_MASTER_KEY` from docker-compose (not needed without encrypted credentials)\",\n      \"command\": [\n        \"opencode\",\n        \"run\",\n        \"--agent\",\n        \"build\",\n        \"--format\",\n        \"json\",\n        \"--session\",\n        \"ses_23fdc9eceffeHMOxZ1mCxH0PdG\",\n        \"Once finished coding and testing, you must make sure it runs, both locally, and that docker build also finishes successfully, and docker compose is able to run.\\n\\nDo not ask for confirmation. Do not stop with a plan. Fulfill the request and finish.\\n\\nThis is phase 2 of 2 and a continuation of the existing project in the current working directory. Do not regenerate the app. Do not create a second app. Validate and fix the current codebase in place.\\n\\nUse environment variables so RubyLLM actually works. Source ~/.config/zsh/secrets only to load the required environment, especially OPENROUTER_API_KEY. Do not print secret values, do not copy secret file contents into the repo, and do not commit secrets into files, logs, Dockerfiles, compose files, or README examples.\\n\\nValidate the project end-to-end in this order:\\n- run the local app in a way that proves it boots\\n- make any fixes needed so it boots cleanly\\n- make sure `docker build` finishes successfully\\n- make sure `docker compose up --build` is able to run\\n\\nIf one step passes, move to the next without asking for confirmation. If something fails, fix it and continue. Only stop when you have actually completed the validation work or you hit a hard blocker you cannot resolve from inside the workspace.\"\n      ],\n      \"continued_from_session\": \"ses_23fdc9eceffeHMOxZ1mCxH0PdG\",\n      \"elapsed_seconds\": 279.29,\n      \"ended_at\": \"2026-04-24T15:48:00+00:00\",\n      \"exit_code\": 0,\n      \"finish_reason\": \"stop\",\n      \"model\": {\n        \"id\": \"openrouter/xiaomi/mimo-v2.5-pro\",\n        \"label\": \"Xiaomi MiMo V2.5 Pro\",\n        \"provider\": \"openrouter\",\n        \"selection_reason\": \"Xiaomi's flagship coding model. $1/$3 per M, 1M context, tool calling supported. Brand-new family we haven't tested \\u2014 competitive pricing with mid-tier Chinese models like Kimi and GLM.\",\n        \"slug\": \"mimo_v2_5_pro\"\n      },\n      \"no_progress_timeout_seconds\": 360,\n      \"opencode_session_id\": \"ses_23fdc9eceffeHMOxZ1mCxH0PdG\",\n      \"output_tokens_per_second\": 0.63,\n      \"paths\": {\n        \"opencode_config\": \"config/opencode.benchmark.json\",\n        \"project_dir\": \"results/mimo_v2_5_pro/project\",\n        \"prompt\": \"results/mimo_v2_5_pro/followup-prompt.txt\",\n        \"stderr\": \"results/mimo_v2_5_pro/followup-opencode-stderr.log\",\n        \"stdout\": \"results/mimo_v2_5_pro/followup-opencode-output.ndjson\"\n      },\n      \"phase\": \"phase2\",\n      \"preview_output_tokens_per_second\": 68.74,\n      \"preview_output_tokens_per_second_average\": 51.05,\n      \"project_summary\": {\n        \"file_count\": 1554,\n        \"present\": {\n          \"app_dir\": true,\n          \"compose_yaml\": false,\n          \"compose_yml\": false,\n          \"docker_compose_yaml\": false,\n          \"docker_compose_yml\": true,\n          \"dockerfile\": true,\n          \"gemfile\": true,\n          \"javascript_dir\": true,\n          \"readme_lower\": false,\n          \"readme_md\": true,\n          \"routes\": true,\n          \"tests_dir\": true,\n          \"views_dir\": true\n        },\n        \"works_as_intended\": \"yes\",\n        \"works_note\": \"Rails app, tests, README, and container files detected.\"\n      },\n      \"prompt_sha256\": \"e2f60835f36832ba1242d6f23a02bd7958611c52f2db122a3df93f8727dab9b5\",\n      \"stall_reason\": null,\n      \"stalled\": false,\n      \"started_at\": \"2026-04-24T15:43:21+00:00\",\n      \"status\": \"completed\",\n      \"stderr_excerpt\": \"\",\n      \"timed_out\": false,\n      \"timeout_seconds\": 5400,\n      \"tokens\": {\n        \"cache\": {\n          \"read\": 79936,\n          \"write\": 0\n        },\n        \"input\": 323,\n        \"output\": 177,\n        \"reasoning\": 11,\n        \"total\": 80447\n      },\n      \"tokens_per_second\": 288.04\n    }\n  ],\n  \"preview_output_tokens_per_second\": 68.74,\n  \"preview_output_tokens_per_second_average\": 51.05,\n  \"primary_prompt_sha256\": \"d25f119447215ebf47477c1ce61b24f801bfcb9336467f5b019d554f3c83537c\",\n  \"project_summary\": {\n    \"file_count\": 1554,\n    \"present\": {\n      \"app_dir\": true,\n      \"compose_yaml\": false,\n      \"compose_yml\": false,\n      \"docker_compose_yaml\": false,\n      \"docker_compose_yml\": true,\n      \"dockerfile\": true,\n      \"gemfile\": true,\n      \"javascript_dir\": true,\n      \"readme_lower\": false,\n      \"readme_md\": true,\n      \"routes\": true,\n      \"tests_dir\": true,\n      \"views_dir\": true\n    },\n    \"works_as_intended\": \"yes\",\n    \"works_note\": \"Rails app, tests, README, and container files detected.\"\n  },\n  \"prompt_sha256\": \"e2f60835f36832ba1242d6f23a02bd7958611c52f2db122a3df93f8727dab9b5\",\n  \"session_exported\": true,\n  \"stall_reason\": null,\n  \"stalled\": false,\n  \"started_at\": \"2026-04-24T15:43:21+00:00\",\n  \"status\": \"completed\",\n  \"stderr_excerpt\": \"\",\n  \"timed_out\": false,\n  \"timeout_seconds\": 5400,\n  \"tokens\": {\n    \"cache\": {\n      \"read\": 79936,\n      \"write\": 0\n    },\n    \"input\": 323,\n    \"output\": 177,\n    \"reasoning\": 11,\n    \"total\": 80447\n  },\n  \"tokens_per_second\": 288.04\n}\n"}}}}