Agent skill repository index
Skill aAAaqwq/AGI-Super-Team/skills/agent-skill-repository-index
Find and compare Daniel's reviewed GitHub skill sources. Use for high-star skill discovery, link checks, or safe installation, update, and removal of one selected skill.From its SKILL.md
npx -y skills add aAAaqwq/AGI-Super-Team --skill agent-skill-repository-indexAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- runs commandsInstructs the agent to run 3 commands, including `python3 scripts/verify_repository_index.py --repo-root /absolute/path/to/repos` and 2 more.
SKILL.md
3.5 KB, 721 tokens by cl100k_base, as published. Nobody here has run it
Daniel's Recommended High-Star GitHub Skills
Route agents to reviewed upstream repositories without globally activating every repository. Treat popularity as a discovery signal, never as proof of quality or safety.
Load Only What You Need
- Read references/repositories.md to find and compare sources.
- Read references/star-snapshot.md only when the user asks about popularity or ranking.
- Read references/installing.md before installing, updating, linking, migrating, or removing a skill.
- Run
python3 scripts/verify_repository_index.py --repo-root /absolute/path/to/reposto verify index-to-clone identity. Add--remotewhen current GitHub reachability matters.
Fast Workflow
- Resolve intent: discovery, comparison, installation, update, removal, or link verification.
- Search already installed skills first. Reuse an equivalent Codex-native skill instead of adding a duplicate.
- Shortlist at most three sources by capability, runtime compatibility, maintenance, license, and risk class. Use stars only as a tie-breaker.
- If a repository is an
awesome-*catalog or has no rootSKILL.md, use it for discovery only. Trace the selected item to its original upstream. - Inspect one candidate directory completely:
SKILL.md, adjacent resources, license, Git remote, commit, worktree state, scripts, hooks, dependencies, credentials, network actions, and persistent state. - Classify it as
DAILY,LIBRARY,QUARANTINE, orDUPLICATE. Do not installQUARANTINEcapabilities without explicit authorization for their runtime effects. - Follow references/installing.md. Install only the reviewed skill subdirectory, not the entire aggregator.
- Validate metadata and resources, then test one positive trigger and one negative trigger.
- Return an installation receipt containing upstream URL, local source, subpath, commit, license, class, target, install method, adaptations, checks, update method, and rollback method.
Efficient Search
Search metadata before opening files:
rg -n --glob 'SKILL.md' '^(name|description):.*KEYWORD' /absolute/path/to/repos
Then inspect only the chosen skill directory. Scan risky behavior without printing secret values:
rg -l --hidden '(curl.+\|\s*(sh|bash)|sudo\b|rm\s+-rf|cookies?|auth|token|secret|hook|auto.?update|deploy|tunnel|daemon|memory)' /absolute/path/to/candidate
Decision Rules
- Prefer the original upstream, a Codex-native plugin, or a single passive instruction skill.
- Prefer a symlink for a clean reviewed local source that should update with its repository; prefer a normalized copy when Codex-specific adaptation is required.
- Keep catalogs, full runtimes, hooks, MCP servers, auto-updaters, deployers, tunnels, browser profiles, and persistent-memory systems inactive during discovery.
- Preserve dirty repositories and existing targets. Never overwrite or delete them to complete an installation.
- Fetch live star counts only when the user asks for a current ranking. Label the bundled figures as Daniel's July 2026 snapshot.
For “redesign this landing page,” invoke the selected design skill. For “which high-star design skill repository does Daniel recommend, and install the safest option,” invoke this skill first.
What ships with it: 5 files
17.4 KB alongside SKILL.md, 1 of them executable
agents/
- openai.yaml301 B
references/
- installing.md4.7 KB
- repositories.md6.7 KB
- star-snapshot.md1.7 KB
scripts/
- verify_repository_index.pyruns4.1 KB
Gives 0 of the 12 instructions most context ai engineering skills give in 721 tokens
Counted across 1,328 of the 2,349 authors here whose files we hold, read 2026-09-06
- Dispatch a fresh subagent for each taskin 76 of 1328, across 59 files
- Perform spec compliance review before code quality reviewin 44 of 1328, across 34 files
- Dispatch a final code reviewer after all tasksin 38 of 1328, across 26 files
- Answer subagent questions before allowing implementationin 36 of 1328, across 26 files
- Use the least powerful model capable of the taskin 33 of 1328, across 26 files
- Create a TodoWrite list for all tasksin 32 of 1328, across 22 files
- Perform a task review after each implementationin 31 of 1328, across 24 files
- Extract all tasks and context from the planin 29 of 1328, across 20 files
- Provide full task text to subagentsin 28 of 1328, across 20 files
- Use git worktrees for isolated workspacesin 25 of 1328, across 20 files
- Specify the model explicitly when dispatching a subagentin 23 of 1328, across 18 files
- Execute all tasks from the plan without stoppingin 21 of 1328, across 16 files
Said here and by no other author read
- Read repository references to find and compare sources
- Shortlist at most three sources by capability and risk
- Inspect candidate directories for security and metadata
- Classify skills as daily, library, quarantine, or duplicate
- Install only the reviewed skill subdirectory
- Validate metadata and test positive and negative triggers
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.