Agent skill

Ijfw Summarize

by FerroxLabs in FerroxLabs/ijfw

Generate optimized project context from codebase scan. An agent skill from FerroxLabs/ijfw.

MITAuto-check passedAgent Workflows

Install Ijfw Summarize

skills CLI
$ npx skills add FerroxLabs/ijfw --skill ijfw-summarize -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install FerroxLabs/ijfw ijfw-summarize --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/FerroxLabs/ijfw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/codex/skills/ijfw-summarize .claude/skills/ijfw-summarize && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
ijfw-summarize
GitHub stars
212
Token cost
~326 tokens
SKILL.md length
91 words
Files
1
Skills in repo
38
Repo updated
First seen
Licence
MIT

At a glance

Generate optimized project context from codebase scan. An agent skill from FerroxLabs/ijfw.

  • Works in 4 steps: Read: package.json, tsconfig.json,… → Scan: directory structure (2 levels… → Detect: language, framework, database,… → …
  • Tasks that involve Agent instruction files
  • SKILL.md covers Process and Output
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Ijfw Summarize is an agent skill from FerroxLabs/ijfw. Generate optimized project context from codebase scan. Trigger: new project, no CLAUDE.md, /ijfw-summarize

Its SKILL.md is about 330 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Agent instruction files. The repository describes itself as: IJFW — It Just Fcking Works. Ferrox Labs' local-first infrastructure for AI coding agents: shared memory, smart routing, multi-AI cross-audits, disciplined workflow. The licence is MIT.

When your agent uses it

  • Tasks that involve Agent instruction files

Example prompts

  • “/ijfw-summarize”

Requirements

  • Docker

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Read: package.json, tsconfig.json, Cargo.toml, pyproject.toml, go.mod, Dockerfile,
  2. Scan: directory structure (2 levels deep), test framework, linter config, CI config.
  3. Detect: language, framework, database, ORM, auth approach, deployment target.
  4. Identify: key directories, entry points, API route patterns, shared utilities.

What it can do on your machine

Read from SKILL.md and the folder at commit eda62f3. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Ijfw Summarize loads about 326 tokens when it runs. Until then it costs about 30 tokens; SKILL.md has 91 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~30
When it runs · the whole SKILL.md, loaded when a task matches
~326

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from FerroxLabs/ijfw at commit eda62f3, republished under its MIT licence (© FerroxLabs). 91 words, ~326 tokens.

Download SKILL.mdSave it as .claude/skills/ijfw-summarize/SKILL.md (or your agent's skills folder).
name
ijfw-summarize
description
Generate optimized project context from codebase scan. Trigger: new project, no CLAUDE.md, /ijfw-summarize

Scan the codebase and generate an optimized project context file.

Process

  1. Read: package.json, tsconfig.json, Cargo.toml, pyproject.toml, go.mod, Dockerfile, docker-compose.yml, .env.example, Makefile -- whatever exists.
  2. Scan: directory structure (2 levels deep), test framework, linter config, CI config.
  3. Detect: language, framework, database, ORM, auth approach, deployment target.
  4. Identify: key directories, entry points, API route patterns, shared utilities.

Output

Write a platform context file (CLAUDE.md, GEMINI.md, or equivalent) with:

markdown
# Project Context

Stack: <framework> / <language> / <database>
Architecture: <pattern -- monolith, microservices, serverless, etc.>
Entry: <main entry point(s)>
Tests: <framework + command to run>
Lint: <tool + command>

## Structure
<key directories and their purpose, 1 line each>

## Patterns
<established code patterns to follow, 1 line each>

## Key Files
<important files a new contributor should know about>

Rules:

  • Max 50 lines. This loads every session.
  • No boilerplate explanations. Just facts.
  • If uncertain about a pattern, omit it -- don't guess.

© FerroxLabs, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in codex/skills/ijfw-summarize of FerroxLabs/ijfw.

Open the folder on GitHubat commit eda62f3

Compare with similar skills

Ijfw Summarize next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Ijfw Summarize compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Ijfw Summarize this skillFerroxLabs/ijfw212—~326Automated safety check: PassMIT
Using Agent Skillsaddyosmani/agent-skills103k4 repos~2.4kAutomated safety check: PassMIT
Claude ReflectBayramAnnakov/claude-reflect1.7k2 repos~627Automated safety check: PassMIT
Writing For Agentsbestofjs/bestofjs3.1k19 repos~2.7kAutomated safety check: PassMIT
Neat-Freak Knowledge CloseoutKKKKhazix/khazix-skills21k—~1.9kAutomated safety check: PassMIT
Task Observerrebelytics/one-skill-to-rule-them-all3.2k1 repos~12kAutomated safety check: PassCC-BY-4.0

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Categories

Questions about Ijfw Summarize

What does Ijfw Summarize do?

Generate optimized project context from codebase scan. An agent skill from FerroxLabs/ijfw. Ijfw Summarize is an agent skill from FerroxLabs/ijfw. Generate optimized project context from codebase scan.

When should I use Ijfw Summarize?

Ijfw Summarize fits situations like: tasks that involve Agent instruction files.

How do I install Ijfw Summarize in Claude Code?

Run `npx skills add FerroxLabs/ijfw --skill ijfw-summarize -a claude-code`. Or copy the skill folder (codex/skills/ijfw-summarize in FerroxLabs/ijfw) into .claude/skills/ijfw-summarize in your project. Claude Code loads it when a task matches its description.

How do I install Ijfw Summarize in Codex?

Run `npx skills add FerroxLabs/ijfw --skill ijfw-summarize -a codex`. Or copy the skill folder (codex/skills/ijfw-summarize in FerroxLabs/ijfw) into .agents/skills/ijfw-summarize in your project. Codex loads it when a task matches its description.

Can I use Ijfw Summarize in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add FerroxLabs/ijfw --skill ijfw-summarize -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ijfw-summarize, .gemini/skills/ijfw-summarize, .github/skills/ijfw-summarize and .opencode/skills/ijfw-summarize in your project.

What does Ijfw Summarize need to run?

SKILL.md names no scripts, command-line tools or credentials: Ijfw Summarize is instructions for the agent only. Our summary lists: Docker.

Does Ijfw Summarize access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Ijfw Summarize safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Ijfw Summarize use?

Ijfw Summarize is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Ijfw Summarize use?

About 326 tokens (SKILL.md is roughly 1.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Ijfw Summarize?

Skills that share tags, products or a category with Ijfw Summarize: Using Agent Skills (addyosmani/agent-skills, 103k stars), Claude Reflect (BayramAnnakov/claude-reflect, 1.7k stars), Writing For Agents (bestofjs/bestofjs, 3.1k stars) and Neat-Freak Knowledge Closeout (KKKKhazix/khazix-skills, 21k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ijfw Summarize?

FerroxLabs (a GitHub user) maintains it in FerroxLabs/ijfw, which has 212 GitHub stars. The repository holds 38 skills in this directory. The repository was last updated on October 5, 2026.

Source: FerroxLabs/ijfw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.