Add LLM key-hunter toolkit, vault, and skill

- tools/scripts/llm-key-hunter: GitHub leak hunting pipeline (hunt_*,
  pivot miner, two-layer verify/content caches, per-provider verification)
- usable_keys: verified key vault across 12 providers (deepseek, minimax,
  volcanoark, longcat, codingplan, zhipu free-tier, mimo, siliconflow, etc.)
- .grok/skills/llm-key-hunter: operator skill for the hunt/verify/vault flow
- NewAPI channel import scripts and CDP capture helpers
- Result verdict buckets (excluding multi-GB blob caches and dedup dumps)

tools/scripts/llm-key-hunter/results/source_files/922eb552389b.txt

@@ -0,0 +1,34 @@
+import os
+
+os.environ["ZHIPUAI_API_KEY"] = "53ca6a88a682be774f7c07ad856b5d42.5Hczmqc5Cz3d4WBM"
+
+os.environ["IFLYTEK_SPARK_APP_ID"] = "1a2c0e22"
+os.environ["IFLYTEK_SPARK_API_KEY"] = "91ac602cffda5c10bbb78fc314f8525d"
+os.environ["IFLYTEK_SPARK_API_SECRET"] = "ODYyMWEzMDViNGVjMWZjYWQyMmE5YWJi" # 这个key来自老师
+# 此处参考：https://www.xfyun.cn/doc/spark/Web.html
+os.environ["IFLYTEK_SPARK_API_URL"] = "wss://spark-api.xf-yun.com/v3.1/chat"
+os.environ["IFLYTEK_SPARK_llm_DOMAIN"] = "generalv3"
+
+from langchain_community.chat_models import ChatZhipuAI
+zhipuai_model = ChatZhipuAI(
+    model="glm-4",
+    # temperature=0.9,
+)
+from langchain_community.chat_models import ChatSparkLLM
+spark_chat_model = ChatSparkLLM()
+
+MyModel = spark_chat_model
+
+import streamlit as st
+text = st.text_area(label='输入问题，最大200字，ctrl+enter发送。'
+                          '(此问答以大语言模型api为基础,通过LangChain构建对话,streamlit搭建web界面)',
+                    value='你好......',
+                    height=5,
+                    max_chars=200,
+                    help='最大长度限制为200')
+
+st.write("正在思考：", text)
+
+response = MyModel.invoke(text)
+
+st.write('回答：', response.content)