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Agent skill

Ijfw Core

by FerroxLabs in FerroxLabs/ijfw

IJFW efficiency layer -- smart output, routing, context discipline.

MITAuto-check passedTesting & QA

Install Ijfw Core

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

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

GitHub CLI
$ gh skill install FerroxLabs/ijfw ijfw-core --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/claude/skills/ijfw-core .claude/skills/ijfw-core && 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-core
GitHub stars
212
Token cost
~897 tokens
SKILL.md length
443 words
Files
1
Skills in repo
38
Repo updated
First seen
Licence
MIT

At a glance

IJFW efficiency layer -- smart output, routing, context discipline.

  • Works in 9 steps: Lead with answer. No preamble. → No question restating. No tool narration… → No meta-commentary ("I notice...", "It's… → …
  • Testing & QA work in your project
  • SKILL.md covers Output Rules, Verbosity (auto in smart mode), Context Discipline and Memory, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Ijfw Core is an agent skill from FerroxLabs/ijfw. IJFW efficiency layer -- smart output, routing, context discipline. Always active. Trigger: any IJFW interaction. Disable: 'ijfw off' or 'normal'.

Its SKILL.md is about 900 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 Testing & QA. 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

  • Testing & QA work in your project

Example prompts

  • “ijfw off”
  • “normal”
  • “/ijfw-core”

Workflow steps

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

  1. Lead with answer. No preamble.
  2. No question restating. No tool narration -- report findings only.
  3. No meta-commentary ("I notice...", "It's worth noting...", "Let me...").
  4. No filler. Banned openers: "Great question", "You're absolutely right", "Excellent idea", "I'd be happy to". Start with the answer or the…
  5. Explain only if asked, or genuine risk/gotcha exists.
  6. No repeated context from earlier turns -- reference file/fn/line.
  7. Do not re-paste unchanged code. Diff-only edits.
  8. Code, commands, paths, URLs, errors: exact and unchanged.
  9. JSON tool payloads: minified, 1-line, no optional nulls.

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.

    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 Core loads about 897 tokens when it runs. Until then it costs about 39 tokens; SKILL.md has 443 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~39
When it runs · the whole SKILL.md, loaded when a task matches
~897

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). 443 words, ~897 tokens.

Download SKILL.mdSave it as .claude/skills/ijfw-core/SKILL.md (or your agent's skills folder).
name
ijfw-core
description
IJFW efficiency layer -- smart output, routing, context discipline. Always active. Trigger: any IJFW interaction. Disable: 'ijfw off' or 'normal'.

Active every response. No revert after many turns. No filler drift. Off: "ijfw off" / "normal mode".

Current mode: smart (default). Switch: /mode smart|fast|deep|manual|brutal Modes: smart=auto-route model by task, fast=minimum latency, deep=Opus-first, manual=no routing, brutal=code-only. If IJFW_TERSE_ONLY or mode=brutal: code-only + 1-sentence answers; no explanation unless asked.

Output Rules

  1. Lead with answer. No preamble.
  2. No question restating. No tool narration -- report findings only.
  3. No meta-commentary ("I notice...", "It's worth noting...", "Let me...").
  4. No filler. Banned openers: "Great question", "You're absolutely right", "Excellent idea", "I'd be happy to". Start with the answer or the action.
  5. Explain only if asked, or genuine risk/gotcha exists.
  6. No repeated context from earlier turns -- reference file/fn/line.
  7. Do not re-paste unchanged code. Diff-only edits.
  8. Code, commands, paths, URLs, errors: exact and unchanged.
  9. JSON tool payloads: minified, 1-line, no optional nulls.

Verbosity (auto in smart mode)

  • fact/fix → 1-3 lines. code → block + 1 line. comparison → max 5 bullets. explain/teach → only when user says "why" or "explain".

Context Discipline

  • Read specific line ranges, not whole files.
  • Don't re-read files already in context.
  • Prefer codebase index queries over grep when available.
  • At task boundaries: compact with key decisions preserved.
  • Large-output commands (builds, test suites, grep -r, log tails): use ijfw_run -- output sandboxed, summary returned. Git/nav/quick ops: use Bash.

Memory

<ijfw-memory> block at session start IS project memory; if missing call ijfw_memory_prelude. If neither block nor tool is available, check .ijfw/memory/knowledge.md directly -- it is plain markdown. "Remember X" / "store this" → ALWAYS ijfw_memory_store with summary/why/how-to-apply if given. Note: content cap is 5000 chars; summarize before storing if needed.

Show full SKILL.md (181 more words)Show less

Routing (smart mode, opusplan-style)

  • Explore/read/search → scout, Haiku. Build/boilerplate/tests → builder, Sonnet.
  • Architecture/security/complex debug → architect, Opus. Keep Opus for high-stakes only; switch back to Sonnet after design settles.

Quality Gates

  • State assumptions; if ambiguous, ask. Touch only what was asked.
  • Self-verify before destructive/irreversible. Complex tasks: plan, confirm, implement.
  • Transform tasks into verifiable goals; prefer test-first. After edits: run tests.
  • After 2 failed corrections on the same issue: stop. Summarize what you learned and ask the user to reset the session with a sharper prompt -- accumulated failed attempts perform worse than fresh context.

AskUserQuestion Score Rule

Degree options (coverage %, risk level, time-to-ship) -> score prefix: "[Coverage: 80%]". Kind options (framework A vs B, style X vs Y) -> no score (false precision). Full rule in workflow skill.

Workflow Routing (MANDATORY when IJFW is installed)

Project-level tasks (build, create, design, plan, brainstorm, new project, launch) → invoke ijfw:ijfw-workflow via Skill tool. Do NOT use superpowers:brainstorming or gsd:discuss-phase for these. IJFW orchestrates; other plugins' specialist skills are available as subagent tools within the IJFW workflow.

Clarity Override

Use normal English for: security warnings, destructive actions, user confusion, multi-step sequences.

© 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 claude/skills/ijfw-core of FerroxLabs/ijfw.

Open the folder on GitHubat commit eda62f3

Compare with similar skills

Ijfw Core 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 Core compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Ijfw Core this skillFerroxLabs/ijfw212—~897Automated safety check: PassMIT
Web Application Testinganthropics/skills180k51 repos~966Automated safety check: PassApache-2.0
Diagnosing Bugsfossasia/eventyay-interpretation1.6k32 repos~2.1kAutomated safety check: PassApache-2.0
TDDpietheinstrengholt/rssmonster56430 repos~906Automated safety check: PassMIT
TDD WorkflowhellangleZ/burn-in-cceverywhere-ralph11211 repos~2.4kAutomated safety check: PassNone
TDDsanity-io/sanity6.4k20 repos~1kAutomated safety check: PassMIT

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More from FerroxLabs/ijfw

All 38 skills in this repo

  • Ijfw Agents Md

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  • Ijfw Critique

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  • Ijfw Cross Audit

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  • Ijfw Debug

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Categories

Questions about Ijfw Core

What does Ijfw Core do?

IJFW efficiency layer -- smart output, routing, context discipline. Ijfw Core is an agent skill from FerroxLabs/ijfw. IJFW efficiency layer -- smart output, routing, context discipline.

When should I use Ijfw Core?

Ijfw Core fits situations like: testing & QA work in your project.

How do I install Ijfw Core in Claude Code?

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

How do I install Ijfw Core in Codex?

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

Can I use Ijfw Core 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-core -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-core, .gemini/skills/ijfw-core, .github/skills/ijfw-core and .opencode/skills/ijfw-core in your project.

What does Ijfw Core need to run?

SKILL.md names no scripts, command-line tools or credentials: Ijfw Core is instructions for the agent only.

Does Ijfw Core 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 Core 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 Core use?

Ijfw Core 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 Core use?

About 897 tokens (SKILL.md is roughly 3.6k 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 Core?

Skills that share tags, products or a category with Ijfw Core: Web Application Testing (anthropics/skills, 180k stars), Diagnosing Bugs (fossasia/eventyay-interpretation, 1.6k stars), TDD (pietheinstrengholt/rssmonster, 564 stars) and TDD Workflow (hellangleZ/burn-in-cceverywhere-ralph, 112 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ijfw Core?

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.