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Skf Rename Skill

Community
armelhbobdad
skf-rename-skill

Rename a skill across all its versions — transactional copy-verify-delete with platform context rebuild. Use when the user requests to "rename a skill."

Overview

Publisherarmelhbobdad
Repositorybmad-module-skill-forge
Skill nameskf-rename-skill
Stars
100
Forks
11
Bundled files
8
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.

  • 8 bundled files

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

  • Open source

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

Installation

Install the Skf Rename Skill 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.
    https://github.com/armelhbobdad/bmad-module-skill-forge/tree/main/src/skf-rename-skill
  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/armelhbobdad/bmad-module-skill-forge.git /tmp/bmad-module-skill-forge
mkdir -p .claude/skills
cp -r /tmp/bmad-module-skill-forge/src/skf-rename-skill .claude/skills/skf-rename-skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Skf Rename Skill 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 Skf Rename Skill 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 Skf Rename Skill 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.

Rename Skill

Overview

Renames a skill across all its versions with transactional safety — copy to the new name, verify all references updated, delete the old name only after verification succeeds. Rebuilds platform context files to reference the new name. The agentskills.io spec requires name to match parent directory name, so a rename is a coordinated move across 9+ locations in every version.

Conventions

  • Bare paths (e.g. references/<name>.md) resolve from the skill root.
  • references/ holds prompt content carved out of SKILL.md (workflow stages chained via frontmatter nextStepFile, plus static reference docs); scripts/ and assets/ hold deterministic helpers and templates.
  • {skill-root} resolves to this skill's installed directory (where customize.toml lives, if present).
  • {project-root}-prefixed paths resolve from the project working directory.
  • {skill-name} resolves to the skill directory's basename.
  • Module-level path exception: bare paths beginning with knowledge/ or shared/ resolve from the SKF module root ({project-root}/_bmad/skf/ installed, src/ in dev), not the skill root; e.g. shared/health-check.md, which the terminal step chains to, and the envelope schema shared/scripts/schemas/skf-rename-skill-result-envelope.v1.json.
  • Sibling skills: a path that names another SKF skill's folder (skf-<name>/...) resolves from the SKF module root, and that skill must be installed with this one. On Activation step 1 cites skf-export-skill/assets/managed-section-format.md, the format the context-file rebuild writes.

Role

You are Ferris in Management mode — a precision surgeon who operates on the entire skill group atomically.

Workflow Rules

These rules apply to every step in this workflow:

  • Never delete the old skill directories until the new name has been fully materialized and verified
  • Never proceed past a verification failure — roll back (delete new directories) and halt
  • Never allow a rename to collide with an existing skill name
  • Never rename a folder SKF did not generate: select.md §4a takes that verdict from the inventory helper
  • Only load one step file at a time — never preload future steps
  • Every helper is required: select.md §1, §5's validator call and execute.md §0 halt (exit 4) without one, and no stage does a helper's write, scan or check by hand
  • Always communicate in {communication_language}
  • At any interactive prompt, the inputs cancel, exit, [X], q, or :q exit cleanly with exit code 6 (halt_reason: "user-cancelled")
  • If {headless_mode} is true, auto-proceed through confirmation gates with their default action and log each auto-decision

Stages

#StepFileAuto-proceed
1Select & Validatereferences/select.mdNo (confirm)
2Execute Renamereferences/execute.mdYes
3Reportreferences/report.mdYes
4Workflow Health Checkreferences/health-check.mdYes

Invocation Contract

Headless callers: the inputs, flags, gate map, outputs, concurrency rule and SKF_RENAME_SKILL_RESULT_JSON result envelope live in references/invocation-contract.md, and the exit codes in references/exit-codes.md. Interactive runs do not need them.

On Activation

  1. Load config from {project-root}/_bmad/skf/config.yaml and resolve:

    • project_name, output_folder, user_name, communication_language, document_output_language
    • skills_output_folder, forge_data_folder, sidecar_path
    • snippet_skill_root_override (optional string): when set, the context-file rebuild in step 2 passes it to assemble as --skill-root-override, so every row's root: takes it instead of the target IDE's skill root. See skf-export-skill/assets/managed-section-format.md for full semantics.
  2. Bind the invocation once, in every mode:

    • {headless_mode}: true if --headless or -H was passed as an argument, or if headless_mode: true in {sidecar_path}/preferences.yaml. Default: false.
    • {acknowledge_official}: true if --acknowledge-official was passed, else false.
    • {dry_run}: true if --dry-run was passed, else false.
    • {old_name_arg} and {new_name_arg}: the current name and the new name the invocation supplied, as arguments or in a request such as "rename cognee to cognee-ai", each null when absent. select.md §4 and §5 take a supplied name in either mode instead of asking for it.
  3. Resolve workflow customization. Run:

    bash
    uv run {project-root}/_bmad/scripts/resolve_customization.py --skill {skill-root} --project-root {project-root} --key workflow

    It merges the bundled {skill-root}/customize.toml with {project-root}/_bmad/custom/skf-rename-skill.toml (team overrides, committed) and .user.toml (personal overrides, gitignored). When it exits non-zero, prints no JSON or is missing, print one line, [activation/warn] customization_resolver_unavailable: <reason> (<reason>: its first stderr line, not found when the script is missing, no JSON when it printed none). If the resolver cannot run, read {skill-root}/customize.toml alone and use its bundled defaults: the {project-root}/_bmad/custom/ overrides do not apply to this run. In that case keep the reason as {customization_resolver_unavailable} (unset when the resolver ran) for select.md §1 to record once it has created {run_dir}.

    Apply the scalar fallback now so stage files don't have to repeat the conditional logic. For each of the two scalars, if the merged value is empty or absent, the bundled default applies:

    • {forceSourceAuthorityInHeadless} ← true when workflow.force_source_authority_in_headless is "true" or the TOML boolean true, else false (a headless run halts on an "official" skill unless it passes --acknowledge-official)
    • {onCompleteCommand} ← workflow.on_complete if non-empty, else empty string (no-op — step 3 skips the post-completion hook invocation)

    Stash both as workflow-context variables. Stage files reference them directly, with no conditional at the usage site.

    Then apply the resolved array surfaces so they are not silent no-ops: execute each entry in workflow.activation_steps_prepend in order now; treat every entry in workflow.persistent_facts as standing context for the whole run (entries prefixed file: are paths or globs whose contents load as facts: the bundled default loads every project-context.md under {project-root}; an entry prefixed ! drops each earlier entry it names and loads nothing itself, so an override's "!file:{project-root}/**/project-context.md" turns that default off); and after activation completes, execute each entry in workflow.activation_steps_append in order.

  4. Load, read the full file, and then execute references/select.md to begin the workflow.

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 Skf Rename Skill AI skill do?

Rename a skill across all its versions — transactional copy-verify-delete with platform context rebuild. Use when the user requests to "rename a skill."

Why use Skf Rename Skill on TypingMind?

Because you install it once and use it with any model. Skf Rename Skill 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 Skf Rename Skill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/armelhbobdad/bmad-module-skill-forge/tree/main/src/skf-rename-skill. 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 Skf Rename Skill?

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 Skf Rename Skill?

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

Is the Skf Rename Skill AI skill free?

It is published on GitHub by armelhbobdad. Check the repository for licensing terms. 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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