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LLM token logprobs and calibration. Per-decision confidence, ECE, Brier, reliability diagrams, low-confidence triage.
Analyze LLM token logprobs and calibration. Use for per-decision confidence, ECE, Brier scores, reliability diagrams, and low-confidence triage.
回顾最近 N 天的 Claude Code 使用记录——扫描原始会话数据，按主题分组汇总"我都做了什么"，并从个人操作系统视角输出模式、风险与增删建议。当用户说 /recap、"看看我这几天做了什么"、"回顾一下我最近的会话"、"这两天我用 claude 干了啥"、"活动回顾" 时使用。
Based on SOC occupation classification
| name | vector-store |
| description | Transient vector store service for fast similarity search (FAISS) |
| triggers | ["vector store","faiss","similarity search","vector index"] |
| allowed-tools | curl |
| commands | [{"name":"serve","description":"Start the vector store service","usage":"./run.sh serve"},{"name":"sanity","description":"Run sanity tests","usage":"./sanity.sh"}] |
| metadata | {"port":8600,"endpoints":["/index","/search","/reset","/info"]} |
| provides | ["vector-store"] |
| composes | ["memory","embedding","edge-verifier","task-monitor"] |
Transient vector store service for fast similarity search using FAISS (IndexFlatIP). Designed to be used by other skills (memory, edge-verifier) to accelerate KNN search.
VECTOR_STORE_PORT: Port to listen on (default: 8600)Add vectors to the index.
{
"ids": ["id1", "id2"],
"vectors": [[0.1, 0.2, ...], [0.3, 0.4, ...]],
"reset": false
}
Search for nearest neighbors.
{
"query": [0.1, 0.2, ...],
"k": 10
}
Returns:
{
Clear the index.
Get index stats.