coding-trace-collect
coding-trace-collect is an LLM evaluation & observability skill for AI agents, published by uw-syfi in the TraceLab repository on GitHub. Skillspace rates coding-trace-collect D (64/100) and it passed the safety scan; the rating is based on static analysis only.
Collect, count, and extract Claude Code and Codex CLI local histories into normalized coding-trace JSONL files. Use when running collect_llm_traces.py, extract_claude_rounds.py, extract_codex_rounds.py, collect_all_users_sudo.sh, scanning current-user or all-user homes, choosing output paths, using --fresh-extract or --append-dedup, or troubleshooting extraction counts.
- Grade
- D
- Quality
- 64 / 100
- Safety
- Passed
- GitHub stars
- 44
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- Low-risk patterns
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- mentions secrets in text
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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