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Manage Skills Hub

CommunityPopular
qufei1993
manage-skills-hub

Use this skill whenever an Agent needs to query, find, install, deploy, update, tag, adopt, diagnose, or safely remove Skills Hub content, including natural-language requests to manage Skills for Codex, Claude Code, Cursor, or another Agent. Always use the Skills Hub CLI workflow instead of editing Skill directories or the database.

Overview

Publisherqufei1993
Repositoryskills-hub
Skill namemanage-skills-hub
Stars
1.7K
Forks
196
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by qufei1993 on GitHub. Read the source before you install it.

Installation

Install the Manage Skills Hub 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/qufei1993/skills-hub/tree/main/skills/manage-skills-hub
  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/qufei1993/skills-hub.git /tmp/skills-hub
mkdir -p .claude/skills
cp -r /tmp/skills-hub/skills/manage-skills-hub .claude/skills/manage-skills-hub
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Manage Skills Hub 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 Manage Skills Hub 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 Manage Skills Hub 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.

Manage Skills Hub

Translate the user's requested Skill operation into the trusted skillshub-cli commands below. By default, an AI installation includes syncing to detected, enabled tools in Skills Hub; explicit user scope takes precedence. Keep device sync, automation, credentials, and application settings in the desktop app.

Resolve a trusted CLI before every workflow

  1. Inspect ~/.skills-hub/bin without executing a binary. Only when that directory is completely absent, inspect ~/.skills-hub-dev/bin as the desktop development bridge. These desktop profiles share the Skill library, but keep credentials separate. On Windows expand the user's home directory and use skillshub-cli.exe; otherwise use skillshub-cli. Never switch to another bridge when the selected directory exists but fails validation.
  2. If that bridge directory exists (including a broken link or inaccessible path), require a regular executable binary and both regular stamp files skillshub-cli.version and skillshub-cli.sha256 in that directory. Read only these public stamps. Validate a nonempty version and a 64-digit hexadecimal SHA-256 value, then compute the binary's SHA-256 with the platform's hashing utility and require an exact match. Reject symlinked stamps/binaries and unresolvable paths. Do not execute an unverified binary.
  3. After hash validation, bind $CLI to that absolute binary path and run $CLI --json version. Require exit 0, ok: true, and data.version equal to the version stamp. Missing files, invalid stamps, mismatched hash/version, execution failure, and malformed output mean bridge damaged: fail closed, stop, and ask the user to open Settings → AI management in the desktop app and click Enable in one click to install or repair the CLI bridge. First-time installation or repair requires this explicit click; update the CLI and official Skill explicitly in Settings → AI management. Startup only checks status and does not update them. Never fall back to PATH when the bridge location exists but fails validation. Do not repair or edit stamps yourself.
  4. Only when the desktop bridge directory is completely absent, resolve skillshub-cli from PATH for a CLI-only environment. Bind $CLI to the resolved absolute path and run $CLI --json version. If unavailable, explain installing Skills Hub and enabling AI management in Settings. Do not silently install software.

$CLI below denotes that verified executable, not a literal command or shell fragment. Pass arguments as distinct values; quote paths correctly and never evaluate user input as shell code. Read-only bridge inspection and hashing are the only filesystem work this workflow needs.

Interpret machine results

Use --json for every CLI invocation. Read successful JSON from stdout and failed JSON from stderr; inspect the exit status, ok, stable code, and structured details. Treat message as localized explanatory text, never as a parsing contract. Do not report success without a successful result and a CLI readback.

Exit codes: 0 success (including previews); 2 invalid arguments; 3 missing or ambiguous item; 4 safety/path/content conflict; 5 operation busy; 6 incompatible database; 7 network/authentication/source failure; 10 internal failure. Preserve unknown error codes and details rather than guessing. --json never implies confirmation.

Query and choose

Run read-only queries directly:

text
$CLI --json skills list
$CLI --json skills show <name-or-id>
$CLI --json skills search <query> --limit 20
$CLI --json skills status <name-or-id>
$CLI --json skills check <name-or-id>
$CLI --json skills check --all
$CLI --json agents list
$CLI --json doctor
$CLI --json version

Use list filters --tag, --source, --agent, --untagged, or --status when needed. Prefer returned full Skill IDs. On AMBIGUOUS_SKILL, show candidates and resolve the user's choice; never choose an arbitrary match.

Install and deploy

An AI installation is complete after library installation AND deployment to the selected tools. The CLI exposes these as separate commands; skills install alone still only adds to the library. Install a single Skill when the user explicitly requests it:

text
$CLI --json skills install <local-path-or-git-ref>
$CLI --json skills install <repo-ref> --subpath <skill-path>

Use explicit local paths (./, ../, absolute, or ~/), Git references, or supported owner/repo shorthand. On MULTI_SKILLS, show details.candidates and use the selected subpath; never automatically install every candidate. Read back with skills show using the returned ID.

Resolve the target set for each installation request:

User requestTarget selection
Explicitly library-only / no syncInstall and read back only; do not deploy or remove existing deployments.
Names particular toolsUse only those returned Agent keys; do not add default tools. If a named tool is missing, undetected, or disabled, report it without enabling it or creating its directory.
No tools named, including “install” or “sync to all tools”Run agents list; select exactly data.agents entries where BOTH detected and enabled are true, including eligible custom tools. Never use the full supported-tool catalog or assume the current Agent is the only target.

Use global scope by default. If the user specifies a project, use its absolute path with --project for every deployment; ask for the path if unclear. Report unsupported project targets without falling back to global. If no eligible tools exist, keep the installed library copy and clearly report “installed, not synced: no enabled detected tools”; do not enable tools, create uninstalled tool directories, or claim sync success.

After installation and skills show, preview deployment to the resolved Agent keys using skills deploy ... --dry-run. For an ordinary preview within the selected scope, proceed without asking the user to choose tools again. If shared physical directories affect tools outside that set (especially disabled tools), explain the additional impact and obtain confirmation before executing that affected deployment. On conflicts, preserve existing files and report the blocked targets; never force an overwrite. After deployment, read back skills status. For multiple selected Skills, complete this sequence for each and summarize installed, synced, failed, and skipped results separately. On a deployment error, read back actual status and report the library copy as installed but sync incomplete; do not reinstall or claim that all targets succeeded.

text
$CLI --json skills deploy <skill-id> --agent codex
$CLI --json skills deploy <skill-id> --agent codex --agent cursor --dry-run
$CLI --json skills deploy <skill-id> --agent codex --project <absolute-project-path>
$CLI --json skills undeploy <skill-id> --agent codex

For standalone deployment requests, use explicitly named tools; “all tools” means the same detected-and-enabled selection above. If neither is given, ask which tools. The installation default does not authorize changing unrelated existing Skills. For batch undeploy, first run the exact request with --dry-run, show all targets, obtain confirmation, and then run it without --dry-run. Deployment commands do not accept --yes or --all; do not invent flags or add deployment flags to skills install. Read back skills status after deployment or undeployment. Undeploy retains the library copy.

Update

For one requested Skill, run skills check <skill-id>, then skills update <skill-id>, and read back skills show and skills status. For a batch, always run skills check --all, show the affected Skills and held-back changes, and obtain confirmation before skills update --all. The check is the supported batch preview; update does not accept --dry-run or --yes.

Stop on UPDATE_HELD_BACK: files would be removed or unsafe changes detected. Keep the old version and guide the user to review in the desktop app. Never add --force or manually remove extra files to make an update pass.

Adopt existing Skills

text
$CLI --json skills adopt <agent-skills-dir> --dry-run
$CLI --json skills adopt <agent-skills-dir> --yes

Show the preview's candidates and exclusions, obtain confirmation of the exact scope, and only then execute with --yes. Managed sources/targets are excluded automatically. Adopt records unknown external content as local; never invent a Git origin. Verify the returned IDs using skills show.

Tags

Execute explicitly requested single-Skill tag changes and tag renames, then read back:

text
$CLI --json skills tag add <skill-id> <tag>...
$CLI --json skills tag remove <skill-id> <tag>...
$CLI --json skills tag set <skill-id> <tag>...
$CLI --json skills tag list <skill-id>
$CLI --json skills tag list
$CLI --json skills tag rename <old> <new>
$CLI --json skills tag delete <tag> --dry-run
$CLI --json skills tag delete <tag> --yes

For tag deletion, show the affected Skill count and obtain confirmation before --yes. Respect case-insensitive tag matching; do not create duplicate spellings to bypass constraints.

Safe removal and this Skill's setup

text
$CLI --json skills remove <skill-id> --dry-run
$CLI --json skills remove <skill-id> --yes
$CLI --json setup --agent codex
$CLI --json setup --agent codex --remove --dry-run
$CLI --json setup --agent codex --remove --yes

For removal, show the central directory, all deployed targets, and recycle-bin record from the preview. Obtain confirmation before --yes; reuse prior authorization only when it clearly covers that exact reviewed scope. Skills go into the Skills Hub recycle bin; restoration and permanent deletion belong to the desktop app. Verify removal using skills list or the expected SKILL_NOT_FOUND response.

Setup installs the bundled official Skill and deploys only to requested Agents. Removing setup undeploys the official Skill from the named Agents while retaining its library copy. Preview setup removal, confirm, then use --yes. Never remove a same-name unmanaged directory or an edited bundled copy.

Recover safely

  • TARGET_CONFLICT: report the actual safe details.path and reason. Ask the user to review the conflicting content in the desktop app; do not delete, rename, overwrite, or adopt it automatically.
  • UPDATE_HELD_BACK: report the affected Skill and removal count; leave content intact for desktop review.
  • OPERATION_BUSY: report that another operation owns the lock; wait for completion or let the user retry. Never remove lock files, kill the desktop app, or run an unbounded retry loop.
  • CONFIRMATION_REQUIRED: present details.plan, obtain confirmation, and repeat with the supported confirmation flag.
  • PLAN_STALE: create and review a fresh preview; prior confirmation is not authorization for changed scope.
  • AUTH_REQUIRED: direct the user to configure credentials in the desktop app. Never request a Token in chat, command arguments, files, URLs, or logs.
  • INCOMPATIBLE_DATABASE: request a compatible/current CLI or desktop version; never edit the schema or downgrade the database.
  • Failed multi-step writes: report rollback/recovery details and preserved backup paths. Do not automatically retry destructive work or remove recovery content.

Boundaries

Never access SQLite directly, execute SQL, or use cp, rm, ln, scripts, or manual filesystem edits to change the central library or Agent directories. These bypass ownership, locks, rollback, and recycle-bin protection. Do not implement CLI business logic yourself.

Never read, print, store, or request credentials, OAuth codes, Authorization headers, private keys, or credential-bearing URLs. The CLI may use existing secure credentials only during a user-requested supported network operation.

Do not expose device sync, sync conflict resolution, auto tasks, scheduled updates, proxy/storage/tool configuration, account configuration, or permanent recycle-bin cleanup through this Skill. Direct those requests to the desktop app. Never invent sync, credential commands, force overwrite switches, or deployment to the entire supported-tool catalog. Default installation targets are limited to detected AND enabled tools.

Frequently asked questions

What does the Manage Skills Hub AI skill do?

Use this skill whenever an Agent needs to query, find, install, deploy, update, tag, adopt, diagnose, or safely remove Skills Hub content, including natural-language requests to manage Skills for Codex, Claude Code, Cursor, or another Agent. Always use the Skills Hub CLI workflow instead of editing Skill directories or the database.

Why use Manage Skills Hub on TypingMind?

Because you install it once and use it with any model. Manage Skills Hub 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 Manage Skills Hub in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/qufei1993/skills-hub/tree/main/skills/manage-skills-hub. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Manage Skills Hub?

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 Manage Skills Hub?

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

Is the Manage Skills Hub AI skill free?

Yes. It is published on GitHub by qufei1993 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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