dial9-toolkit
dial9-toolkit is a Runtime diagnostics & profiling skill for AI agents, published by dial9-rs in the dial9 repository on GitHub. Skillspace rates dial9-toolkit C (74/100) and it passed the safety scan; the rating is based on static analysis only.
JavaScript analysis toolkit for parsing and analyzing dial9 Tokio runtime traces. Always start trace diagnosis with analyzeTraces() from analyze.js, then use parseTrace() and lower-level helpers only to confirm assumptions or drill into raw events.
- Grade
- C
- Quality
- 74 / 100
- Safety
- Passed
- GitHub stars
- 409
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
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
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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