ijfw-metrics

ijfw-metrics is an LLM evaluation & observability skill for AI agents, published by FerroxLabs in the ijfw repository on GitHub. Skillspace rates ijfw-metrics D (61/100) and it passed the safety scan; the rating is based on static analysis only.

Internal session metrics tracking. Auto-triggered at session boundaries. Tracks tokens, agent usage, efficiency gains. View with /ijfw-status.

Grade
D
Quality
61 / 100
Safety
Passed
GitHub stars
198

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.

View source on GitHubFerroxLabs/ijfw

Our review

Architecture
94 / 100
Maturity
Basic: a single SKILL.md
Security scan
Low-risk patterns
License
MIT
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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