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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.

Install / Use

npx skills add qufei1993/skills-hub --skill manage-skills-hub

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

94/100

Category

Automation

Supported Platforms

Claude Code
Cursor
OpenAI Codex

Our assessment of manage-skills-hub

manage-skills-hub scores 94/100 on our quality scale, 431st of 3,055 Automation skills we index (top 15%).

Its SKILL.md is 12 KB long, well organised into 11 sections with 6 code examples: a thorough specification that gives an agent plenty to work with.

With 1,696 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
14/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 8 days ago, so manage-skills-hub is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

manage-skills-hub compared with similar skills

All 4 of these similar skills score higher than manage-skills-hub; compare them before choosing.

SkillScoreStarsUpdatedFormat
manage-skills-hub (this skill)by qufei1993941.7k8d agoSKILL.md
Agent-Reachby Panniantong10088.1k17d agoCLAUDE.md
rufloby ruvnet10073.7ktodayCLAUDE.md
Scraplingby D4Vinci10085.2k1d agoMCP Server
algorithmic-artby anthropics100177.9k10d agoSKILL.md

Frequently asked questions

How do I install manage-skills-hub?
Run npx skills add qufei1993/skills-hub --skill manage-skills-hub. The install tabs above show the steps for each supported agent.
Which AI agents does manage-skills-hub work with?
It is written for Claude Code, Cursor and OpenAI Codex, as a SKILL.md file. Other agents that read the same format can often use it too.
Is manage-skills-hub safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is manage-skills-hub still maintained?
The repository was last updated 8 days ago, so manage-skills-hub is actively maintained.

name: manage-skills-hub description: 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.

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:

$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:

$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 request | Target selection | | --- | --- | | Explicitly library-only / no sync | Install and read back only; do not deploy or remove existing deployments. | | Names particular tools | Use 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.

$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

$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:

$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

$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 n

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars1.7k
CategoryAutomation
Updated8d ago
Forks194

Languages

Rust

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions