coding-trace-sanitize
coding-trace-sanitize is a Fine-tuning & training data skill for AI agents, published by uw-syfi in the TraceLab repository on GitHub. Skillspace rates coding-trace-sanitize D (64/100) and it passed the safety scan; the rating is based on static analysis only.
Sanitize normalized coding-trace JSONL rows for public sharing. Use when preparing trace/llm_round_trace*.jsonl outputs for release, removing local paths, pseudonymizing user identifiers, dropping tools[].input, replacing session/round/tool/project identifiers with stable pseudorandom values, choosing deterministic versus random sanitizer seeds, or checking what sensitive fields remain after sanitize_round_trace.py.
- 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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