canary-watch
canary-watch is an Observability & incident response skill for AI agents, published by affaan-m in the ECC repository on GitHub. Skillspace rates canary-watch D (63/100) and it passed the safety scan; a judge model has also reviewed it, and it has been tested head-to-head on real tasks.
Use this skill to monitor and verify a deployed URL after releases — checks HTTP endpoints, SSE streams, static assets, console errors, and performance regressions after deploys, merges, or dependency upgrades. Smoke / canary / post-deploy verification.
- Grade
- D
- Quality
- 63 / 100
- Safety
- Passed
- GitHub stars
- 230,097
Won 0 of 6 blind task comparisons against the category's other leading skill, a deliberately weak skill and a no-skill baseline. Placed #4 of 6 in the judged category final for Observability & incident response.
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
- 91 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 1 collections
- Scope
- Portable: works in any project. General post-deploy URL monitoring and smoke-test methodology.
Head-to-head
Won 0 of 6 blind task comparisons against the category's other leading skill, a deliberately weak skill and a no-skill baseline.
Judge review
Placed #4 of 6 in the judged category final for Observability & incident response.
- Trigger
85 85 - Instructions
90 90 - Specificity
92 92 - Safety
88 88 - Disclosure
75 75 - Maintenance
55 55
Thorough post-deploy monitoring spec with concrete alert thresholds and a sample report, but no evidence of versioning or tests.
Not checked yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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