IJFW Metrics

IJFW Metrics is an AI Engineering skill for Claude Code, published by FerroxLabs in ijfw.

210 stars40 forkson FerroxLabs/ijfwAdded 2026/09/04Repository updated 2026/08/31

ai-agentsai-codingclaude-codecodexcursordeveloper-toolsgemini-cligithub-copilotmcpmcp-servermemorynodejstypescriptwindsurf

Install in seconds

Install IJFW Metrics

Copy IJFW Metrics into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/FerroxLabs/ijfw/tree/main/claude/skills/ijfw-metrics ~/.claude/skills/ijfw-metrics

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/FerroxLabs/ijfw.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: claude/skills/ijfw-metrics/SKILL.md in FerroxLabs/ijfw
Installs to: ~/.claude/skills/ijfw-metrics
Collection: One of 25 skills cataloged from this repository
Category: AI Engineering — 2970 skills

What IJFW Metrics does

IJFW Metrics tracks session-level usage at stop time and summarizes tokens, agent activity, routing savings, and continuity. Use it when you want to review Claude Code performance with /ijfw-status.

IJFW Metrics is cataloged under AI Engineering on DirSkills. IJFW Metrics comes from a repository tagged ai-agents, ai-coding, claude-code, codex and cursor.

Documentation

README

Excerpt

IJFW Metrics -- Internal Tracking

Lightweight metrics captured at session boundaries via hooks. Zero per-turn cost. All tracking happens in the Stop hook.

What We Track

At each session end, append to .ijfw/metrics/sessions.jsonl:

{
  "timestamp": "2026-04-13T14:30:00Z",
  "session_id": "<session-id>",
  "duration_minutes": 45,
  "turns": 23,
  "mode": "smart",
  "effort": "high",
  "agents_dispatched": {
    "scout": 8,
    "builder": 12,
    "architect": 3
  },
  "memory_ops": {
    "stores": 5,
    "recalls": 2,
    "searches": 1
  },
  "skills_loaded": ["ijfw-core", "ijfw-commit", "ijfw-review"],
  "compactions": 1,
  "handoff_generated": true,
  "routing": "OpenRouter + local model"
}

Derived Metrics (calculated on /ijfw-status)

From the JSONL log, compute:

This is the opening of the README. Read the full README on GitHub.

Commands IJFW Metrics provides

Slash commands named in this skill’s SKILL.md, listed in the order they first appear.

/ijfw-status

Frequently asked about IJFW Metrics

What else does FerroxLabs publish alongside IJFW Metrics?
IJFW Metrics is one of 25 skills that DirSkills catalogs from FerroxLabs/ijfw, the repository it ships in. Its siblings there include Auto Memorize, Critique and IJFW AGENTS.md Manager. Each one is a separate skill with its own page in this directory, installs the same way IJFW Metrics does, and is maintained by FerroxLabs in that same repository. The rest of the collection is listed on the FerroxLabs/ijfw page.
How does IJFW Metrics compare to other AI Engineering skills?
IJFW Metrics ranks #2692 by stars among the 2970 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of IJFW Metrics against them. Open each page to compare what they document and how they install.