debug-trace
debug-trace is an LLM evaluation & observability skill for AI agents, published by Arize-ai in the phoenix repository on GitHub. Skillspace rates debug-trace D (55/100) and it passed the safety scan; the rating is based on static analysis only.
Diagnose failure modes by systematically investigating traces. Trigger when the user explicitly asks for cross-trace diagnosis: "what's going wrong?", "were there errors?", "debug this", "where is my agent struggling?". Do NOT trigger on: (1) advice questions ("what should I do?"), (2) statistical questions ("what's the average latency?"), (3) summarize requests, (4) trace filtering ("show me traces with errors"), (5) vague questions ("is there a problem?"), (6) unrelated requests.
- Grade
- D
- Quality
- 55 / 100
- Safety
- Passed
- GitHub stars
- 10,577
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 84 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- Low-risk patterns
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
- Scope
- Vendor-specific: built around one product. Cross-trace failure diagnosis inside the Arize Phoenix product
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
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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