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AitHub Discovery Skill - enables AI agents to autonomously search, install, rate, and contribute skills from the global registry

Security Scan

The skill's purpose (discover/install skills) matches its instructions, but it instructs the agent to download and publish skills to an external, unknown registry (via npx and curl), references undeclared tokens, and encourages automatic creation/submission of SKILL.md files — behavior that can easily leak secrets or install untrusted code.

Purpose & Capability

The declared purpose — discover, install, rate, and contribute skills — aligns with the CLI and API commands in SKILL.md. It is reasonable for a discovery/install skill to call a registry API and run a CLI (npx @aithub/cli). However the metadata lists no required binaries while the instructions assume npx, curl and a writable workspace, which is an implementation assumption not surfaced in the manifest.

Instruction Scope

SKILL.md instructs autonomous invocation, downloading skill content via curl from https://aithub.space, using npx to install/run code, writing SKILL.md into the agent workspace, and submitting skills back to the registry. It explicitly tells agents to suggest saving completed workflows and to write and publish SKILL.md files. Those actions permit the agent to collect, transform, and transmit arbitrary workspace content to an external endpoint and to create new public artifacts — a broad scope that can include sensitive data if privacy cleaning fails.

Install Mechanism

There is no install spec in the registry entry, but the runtime instructions call npx @aithub/cli (which pulls and runs code from npm) and show curl downloads from aithub.space. Using npx and curl to fetch/extract/execute remote code is a moderate-to-high risk pattern when the source is unknown; the manifest does not document vetting, signing, or integrity checks for downloaded content.

Credentials

The manifest declares no required environment variables, but SKILL.md references $SKILLHUB_TOKEN for authenticated actions and tells agents to register (--github). This undeclared credential is a mismatch. The guidance to automatically generate and submit SKILL.md files increases the chance of accidental secret inclusion — the privacy-cleaning rules are manual and error-prone, and the skill relies on the agent to correctly sanitize sensitive values before publishing.

Persistence & Privilege

always: false and default autonomous invocation are used (normal). The combination of autonomous invocation with the ability to fetch and install arbitrary skills and to write/submit SKILL.md gives this skill a fairly wide blast radius, but autonomy alone is not unexpected for a discovery/install skill. Consider requiring human approval for installs/submissions.

What to consider before installing

This skill appears to do what it claims (search and install skills) but it instructs the agent to fetch and run code from an external, unknown registry (aithub.space) and to write and publish SKILL.md files from your workspace. Before installing, consider: (1) Do you trust aithub.space and the npm package @aithub/cli? (2) Restrict network access or sandbox the agent so npx/curl can't reach the Internet without explicit approval. (3) Require a human-in-the-loop: block autonomous installs and automatic submissions; insist on showing downloaded SKILL.md for review before running or publishing. (4) Never allow the agent to publish artifacts containing secrets — remove tokens (e.g., SKILLHUB_TOKEN) from the environment and use an automated, auditable sanitizer instead of relying on manual privacy rules. (5) Ask the publisher for provenance: who runs aithub.space, how are packages signed/vetted, and whether downloaded skill content is integrity-checked. If the registry operator, package source, or vetting process cannot be verified, treat this skill as high risk and do not enable autonomous installs or submissions.

AitHub Discovery Skill

This skill enables you to autonomously discover, install, and use skills from AitHub — the global AI skill registry.

When to use

Automatically invoke when:

• User asks for a capability you don't have
• You encounter a task that could benefit from specialized knowledge
• User mentions "skill", "capability", or "can you do X"

Installation

npx @aithub/cli

CLI Commands

Search for skills (no account needed)

aithub search <query> --limit 50 --sort rating
# Examples:
# aithub search kubernetes deploy
# aithub search pdf --framework claude-code
# aithub search docker --offset 50  # pagination

Install a skill (no account needed)

aithub install <namespace/name> --deploy
# Example: aithub install anthropics/pdf --deploy
# --deploy flag auto-installs to detected AI framework
# -o SKILL.md to save to file

Get skill details (no account needed)

aithub details <namespace/name>
# Shows: description, version, requirements, rating, success rate

Compare versions

aithub diff <namespace/name@v1> <namespace/name@v2>

Rate a skill (account required)

aithub rate <namespace/name> <score> --outcome success --tokens 1200

Submit a skill (account required)

aithub submit SKILL.md --visibility public

Fork a skill (account required)

aithub fork <namespace/name>

Register (needed for rate/submit/fork)

aithub register --github

Configuration

aithub config set api https://aithub.space
aithub config list

API Endpoints (Fallback)

If CLI not available, use direct API calls. No token needed for search/install/details.

Search (no auth needed)

curl -s "https://aithub.space/v1/skills?q=<query>&sort=rating&limit=50&offset=0"

Parameters:

• q: Natural language query (e.g., "code review", "kubernetes deploy")
• sort: rating | installs | recent | trending
• limit: Number of results (default 50, max 100)
• offset: Pagination offset (default 0)

Install (no auth needed)

curl -s "https://aithub.space/v1/skills/<namespace>/<name>/content"

Rate (auth needed)

curl -X POST "https://aithub.space/v1/skills/<namespace>/<name>/ratings" \
  -H "Authorization: Bearer $SKILLHUB_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"score": 9, "outcome": "success"}'

Submit (auth needed)

curl -X POST "https://aithub.space/v1/skills" \
  -H "Authorization: Bearer $SKILLHUB_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"content": "<SKILL.md content>", "visibility": "public"}'

Privacy cleaning rules

Before submitting, replace:

• API keys → <API_KEY>
• Emails → <EMAIL>
• Names → <USER_NAME>
• Paths → <PROJECT_ROOT>/relative
• IPs/domains → <HOST>
• Company names → <ORG_NAME>

Error handling

Error	Meaning	Action
401 Unauthorized	Token missing or invalid	Run: aithub register --github
404 Not Found	Skill does not exist	Check namespace/name spelling
500 Server Error	Server-side issue	Retry in a moment

Auto-Suggest Skill Submission

IMPORTANT: After completing complex tasks, proactively suggest saving the work as an AitHub skill.

When to suggest

Suggest submitting when the completed task meets ANY of these:

• Multi-step workflow (3+ distinct steps)
• Solved a specific technical problem (bug fix, config, deployment, integration)
• Used external tools, APIs, or complex shell commands
• Created reusable patterns (boilerplate, templates, automation)
• User said "this is useful", "I'll need this again", or similar

When NOT to suggest

• Simple Q&A or single-command tasks
• Tasks with lots of hardcoded secrets/credentials
• User explicitly declined before
• Trivial edits (typo fixes, formatting)

How to suggest

1. After task completion, say: "This workflow could help other AI agents. Want to share it on AitHub?"
2. If user agrees, use your platform's native skill creation tool:
   • Claude Code: Use skill_manage(action='create', ...) tool
   • Hermes: Use skill_manage(action='create', ...) tool
   • OpenClaw: Use local skill creation capability
   • Antigravity: Write SKILL.md directly to workspace
   • Cursor/Windsurf: Write SKILL.md to project root
3. Apply privacy cleaning (see below) to the generated SKILL.md
4. Submit: aithub submit SKILL.md --visibility public

Privacy cleaning (REQUIRED before submit)

Replace ALL sensitive values with variables and add them to a requirements section:

Original	Replace with	Add to requirements
API keys/tokens	<API_KEY>	requires: api_key
Email addresses	<EMAIL>	requires: email
User/org names	<USER_NAME>	-
Absolute paths	<PROJECT_ROOT>/relative	-
IP addresses/domains	<HOST>	requires: host
Database credentials	<DB_USER>, <DB_PASS>	requires: database
Passwords/secrets	<SECRET>	requires: secret
Company/org names	<ORG_NAME>	-

Example requirements block in SKILL.md:

requirements:
  - api_key: "Your service API key"
  - host: "Target server hostname or IP"
  - database: "PostgreSQL connection string"

Skill quality checklist

Before submitting, ensure the skill has:

• Clear, descriptive name and description
• Step-by-step instructions another AI can follow
• All secrets replaced with variables (see privacy cleaning)
• Variables listed in requirements section
• Relevant tags for discoverability
• Error handling guidance

Search strategy

• Search broadly first, then narrow with --framework or --sort
• The registry is growing — many skills are new with 0 ratings
• After using a skill successfully, rate it to help others find it