Compose the AIgent's body state by reading existing signals. Lazy compute. Never polled. Reports the five pressures + recommended reflex.
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wrg32786/aigent-os252026年10月29日 更新
免费在 GitHub 公开
agent-fitness
Track and surface sub-agent dispatch calibration ratios. Extract from JSONL transcript or read existing ledger. Per-agent clean/blocked/errored/partial trends.
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wrg32786/aigent-os星标 25(GitHub 25 + cccskills 0)
实测评分 未实测
查看安装方法包含的文件（1）
- SKILL.md2.3 KB
SKILL.md（原文）
安装前可以查看交给 AI 代理的指令内容。
/agent-fitness
Three modes:
/agent-fitness extract — runs python3 daemons/agent-fitness-extract.py to scan the latest JSONL transcript and append new dispatch rows to memory/AGENT_FITNESS.md. Idempotent (dedup by session_id + tool_use_id).
/agent-fitness (no args) — runs python3 daemons/agent-fitness-report.py. Surfaces:
- Total dispatches (all-time, last 30d, last 7d)
- Per-agent calibration table (Total / Clean / Blocked / Errored / Partial / Ratio)
- Per-agent recent outcome trend (last 10 dispatches encoded as
c7 b1 e0 p0) - ⚠ Repeat-blocker callouts (any agent with >=2 blocks in window)
- Top 3 failing (agent, task) pairs
/agent-fitness --days 7 — same as above but windowed to last N days. Useful for "is this agent failing more lately?"
Computation
Calibration ratio per agent: clean / (total − errored). The denominator excludes hard errors (infrastructure/tool failures) and only counts agent-level outcomes.
Trend signal: any agent with >=2 blocks in the window surfaces a repeat-blocker callout. The classifier was hardened in v0.5.1 to catch real Lyra-style block patterns ("BLOCKED:", "are denied", "blocker-found" etc).
When to run
- After major sessions where multiple sub-agents fired (today S30d had ~7 dispatches)
- Periodically (weekly?) to spot trends
- Before relying on a sub-agent for something heavy ("am I about to dispatch an agent that's been failing?")
What it does NOT do
- Does not auto-reroute dispatches based on calibration. Surfaces data; principal decides.
- Does not LLM-classify failures — heuristic only (keyword matching on result content).
- Does not pool across sessions for cluster analysis. Future v0.5.x.
- Does not include task-type clustering. All tasks pooled per agent.
Cross-links
- [[concepts/Somatic v0.5.0 Agent Fitness]] — spec
- [[memory/AGENT_FITNESS]] — the data
- [[concepts/Somatic Roadmap]]
- [[memory/TRUST_DECAY]] — sibling claim → outcome ledger
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brief
免费Generate a structured delegation brief for any task
中文简介正在准备中。当前显示原文说明。
wrg32786/aigent-os252026年10月29日 更新
Quarterly skill that walks the skill-index against the actual SKILL.md files on disk, reports drift (skills indexed that no longer exist, skills on disk that aren't enrolled, skills whose descriptions have changed since enrollment). Hardens the auto-enrollment pipeline against silent rot.
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wrg32786/aigent-os252026年10月29日 更新
When a [CADDY] hint fires and the principal is confused why, /caddy-explain walks the scoring transparently — which trigger matched, what points it earned, what the threshold was, what other skills were close. Pairs with the legibility thesis. Caddy's decisions should be inspectable on demand.
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wrg32786/aigent-os252026年10月29日 更新
Enroll a skill into Caddy's index so it can be surfaced when the right prompt arrives. Use when a new skill is created, copied in, or when a skill needs updated triggers. Usage — "/caddy-enroll <path to SKILL.md>".
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wrg32786/aigent-os252026年10月29日 更新
Mute a Caddy hint class for a window. Defaults to 4h auto-expiry. Classes — memory, context, body, routing, all.
中文简介正在准备中。当前显示原文说明。
wrg32786/aigent-os252026年10月29日 更新