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Ccf Skill Forger

CommunityPopular
mikubaka88
ccf-skill-forger

Maintain and audit Codex/CCFA skills, triggers, references, scripts, docs/SVG diagrams, installation dependencies, and release validation. Use for skill维护, GPT model adaptation, and family routing cleanup. Do not perform research writing or review.

Overview

Publishermikubaka88
RepositoryCCFA-Skills
Skill nameccf-skill-forger
Stars
2.6K
Forks
116
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by mikubaka88 on GitHub. Read the source before you install it.

Installation

Install the Ccf Skill Forger AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mikubaka88/CCFA-Skills.git /tmp/CCFA-Skills
mkdir -p .claude/skills
cp -r /tmp/CCFA-Skills/ccf-skill-forger .claude/skills/ccf-skill-forger
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ccf Skill Forger in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ccf Skill Forger on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ccf Skill Forger is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

CCF Skill Forger

Family File Contract

Before writing, resolve the canonical output and one stable working directory per task/artifact. Reuse explicit or established task paths; otherwise use project-root ccfa-workfiles/<purpose>/<artifact-id>/, with source/, assets/, cache/, and build/ only as needed. Update current files in place; do not scatter intermediates or create iteration copies. Preserve inputs and required evidence; clean only verified disposable files created by this task. Use UTF-8 text I/O and check Chinese text after saving or rendering. For file work, apply artifact-contracts.md and reuse the same paths across skill transitions.

Collaboration Contract

Before specialist execution, read and apply ccf-humanization first, then ccf-common. At every handoff, reuse their applicable active rules or refresh missing/changed ones. Both preflights are required even without prose; detailed editing, experiment, and maintenance modes run only when relevant.

Keep one integrating owner and actively use other skills to resolve missing prerequisites or check material findings. Reuse applicable evidence; do not skip necessary groundwork to save tokens. Before finalizing, integrate contributions and verify affected results. Follow the conditional cooperation routes; avoid unrelated stages and duplicate reports.

Invocation Controls

CCFA Handoff Mode: PARTIAL (Recommended). Follow metadata.ccf_skill_controls.handoff_question_mode and ../ccf-common/references/handoff-modes.md when maintaining the CCFA skill family.

When maintaining the CCFA skill family, preserve metadata.ccf_skill_controls in each SKILL.md. Do not add sibling-skill transitions without checking ../ccf-common/references/routing.md, ../ccf-common/references/task-modes.md, ../ccf-common/references/handoff-modes.md, and the denylist-respecting fallback.

If the user disables a skill or asks for writing-only behavior, encode that boundary directly in the edited skill instructions. Do not weaken idea-scope protection in writing skills unless the user explicitly requests that policy change.

When adding sources, update ../ccf-common/references/source-registry.yaml instead of duplicating URL lists in sibling skills. When adding browsing or evidence rules, keep them aligned with ../ccf-common/references/privacy-and-evidence.md.

Never commit machine-specific absolute paths, usernames, expanded home directories, or private local directory names into skills, README files, source registries, diagrams, examples, scripts, or command snippets. Use $CODEX_HOME, $HOME, repo-relative paths, or placeholders that do not identify the user or machine.

Core Rule

Build skills as compact operational guidance for another Codex session. Keep SKILL.md focused on trigger-relevant workflow, decisions, and resource navigation. Put detailed examples, checklists, schemas, policy text, or long instructions in references/ and load them only when needed. This skill also owns CCFA documentation SVG diagrams; do not create a separate runtime drawing skill for repository architecture or workflow diagrams.

Workflow

  1. Clarify the goal with concrete examples. If the user's intent is clear, proceed with reasonable assumptions. Ask only for missing information that changes the skill's scope, location, or required assets.
  2. Choose a skill name and destination. Use lowercase letters, digits, and hyphens only; keep names under 64 characters; check for conflicts in the target skills directory. Default to $CODEX_HOME/skills; if unset, use ~/.codex/skills.
  3. Decide the resource shape:
    • Use only SKILL.md for short, stable procedural guidance.
    • Add references/ for detailed documentation that Codex should read selectively.
    • Add scripts/ only for repeatable deterministic operations or fragile command sequences.
    • Add assets/ only for templates, images, boilerplate, or other files used in final outputs.
  4. Initialize the skill when creating from scratch. Prefer the local skill-creator initializer if available:
powershell
python '<skill-creator-dir>/scripts/init_skill.py' <skill-name> --path '<skills-dir>' --resources references,scripts
  1. Write SKILL.md before filling optional resources. Put all "when to use" trigger wording in the YAML description; the body is loaded only after trigger selection. Apply the functional-naming rule in shared task modes to method introductions and report titles while preserving source records and narrative content. Use imperative instructions and avoid user-facing tutorial prose.
  2. Add resources that directly support the skill. Remove placeholder files and unused directories. Test any script by running it on a small representative example.
  3. Validate changed behavior and structure using the existing family checks. Compare SKILL.md, agent prompts, registry, shared rules, and docs for conflicts. Check real YAML metadata, syntax of existing scripts, resource dependencies, and representative task boundaries; distinguish static checks from actual model evaluation. Preserve public paths and command compatibility. Do not add new files, dependencies, or evaluations when the user limits work to existing surfaces.
  4. Run ccf-common/scripts/check_path_privacy.py before finishing CCFA-family maintenance. Replace any committed local absolute path or username with $CODEX_HOME, $HOME, a repo-relative path, or a non-identifying placeholder.
  5. For CCFA documentation diagrams, work in the CCFA repository checkout and update its tools/build_ccfa_diagrams.py, regenerate all language variants, and screenshot-check rendered SVG output. Use references/svg-style-guide.md; do not hand-edit generated SVGs unless the same change is backported to the generator.

For model adaptation, use current official guidance and store its provenance in the existing source registry. Remove conflicting or redundant instructions before adding new ones. Keep model settings and API-only capabilities in the host; do not hard-code a model in every skill or claim gains without representative comparisons.

Reference Files

Load these files only when the task calls for them:

  • references/design-checklist.md: Use when planning a new skill, reviewing structure, or deciding whether content belongs in SKILL.md, references/, scripts/, or assets/.
  • references/patterns.md: Use when drafting a concrete SKILL.md shape, frontmatter description, or example-driven workflow.
  • references/local-commands.md: Use when scaffolding or validating skills on this machine, especially in PowerShell or Windows paths.
  • references/svg-style-guide.md: Use when maintaining CCFA architecture, workflow, routing, installation, artifact, catalog, or demo SVG diagrams.

Output Style

Use an already approved scheme without another confirmation. For an explicit plan-only request, stop after the reviewable proposal; for authorized maintenance, implement it in the requested existing files. After creation, report the skill name, location, key files, and validation result. If validation cannot run because a local dependency is missing, say exactly what failed and perform the manual checks from references/design-checklist.md.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ccf Skill Forger AI skill do?

Maintain and audit Codex/CCFA skills, triggers, references, scripts, docs/SVG diagrams, installation dependencies, and release validation. Use for skill维护, GPT model adaptation, and family routing cleanup. Do not perform research writing or review.

Why use Ccf Skill Forger on TypingMind?

Because you install it once and use it with any model. Ccf Skill Forger is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ccf Skill Forger in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mikubaka88/CCFA-Skills/tree/main/ccf-skill-forger. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ccf Skill Forger?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ccf Skill Forger?

As many as you like. As long as a model supports skills, you can use Ccf Skill Forger with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ccf Skill Forger AI skill free?

Yes. It is published on GitHub by mikubaka88 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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