← ClaudeAtlas

agent-activity-auditlisted

Audit recent agent transcripts (Claude Code and Codex) to learn how a tool, system, or skill is actually being used in the wild. Surfaces failure modes, friction, success patterns, and concrete improvement candidates from real session data. Use this when you want to improve a developer-facing system that agents interact with regularly.
hyperb1iss/sibyl · ★ 25 · AI & Automation · score 78
Install: claude install-skill hyperb1iss/sibyl
# Agent Activity Audit This skill executes a structured pass over recent agent transcripts to learn what's working and what's hurting. The original audit (May 2026) examined ~30 days of Claude Code and Codex sessions to improve Sibyl itself — see `EXAMPLES.md` for the full reproducible run. The output is a synthesis report grounded in real session evidence, plus per-group findings files you can act on directly. --- ## When to use - You maintain a system that agents call (CLI, MCP server, library, skill) and want signal beyond "did it work?" - You suspect agents are stumbling on something but can't name what. - A planning cycle is about to start and you want product priorities grounded in usage data, not vibes. - A new release shipped and you want to see how it landed in the wild. **Not for:** general code review, security audits, performance benchmarking. This skill reads session transcripts; it doesn't analyze code. --- ## Agent rules (READ FIRST) 1. **Always write artifacts under `contexts/<analysis-name>-<date>/`.** Keep raw scans, episode extracts, and findings in one tree so the analysis is reproducible and the user can replay or extend it. 2. **Filter early, filter hard.** Most transcripts are noise. Triage with cheap grep before spinning up parallel subagents — the goal is to give each subagent ~50-100 KB of focused episode data, not raw multi-MB JSONLs. 3. **Partition by date for the swarm.** Date-based partitions are mutually exclusive, cov