logging-implementation
logging-implementation is an Observability & incident response skill for AI agents, published by irahardianto in the awesome-agv repository on GitHub. Skillspace rates logging-implementation D (57/100) and the safety scan flagged it for review; the rating is based on static analysis only.
Flagged for review. Read the source before running it.
Structured logging implementation patterns: log levels, mandatory context fields (correlationId, userId, duration), security (PII scrubbing), and per-language library choices (Go slog, TypeScript pino, Python structlog). Load when implementing logging in any operation entry point. Prerequisite: logging-and-observability-mandate.md.
- Grade
- D
- Quality
- 57 / 100
- Safety
- Needs review
- GitHub stars
- 150
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
- 80 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- Medium-risk patterns
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- reads environment variables
- mentions secrets in text
Not checked yet
- Category is a classifier prediction; no model has read this skill 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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