Install
$ agentstack add skill-dp-archive-archive-skill-finder ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Skill Finder
Discover and install agent skills from the skills.sh open ecosystem into Skill Compose.
When to Use This Skill
Activate when users:
- Ask "how do I do X?" where an existing skill might help
- Request "find a skill for X" or "is there a skill for X?"
- Ask "can you do X?" for specialized tasks (poster design, data analysis, etc.)
- Want to search for tools, templates, or workflows
- Mention needing help with a specific domain that might have a community skill
Available Scripts
1. Search Skills — find_skills.py
Search the skills.sh ecosystem for skills matching a query.
python scripts/find_skills.py [--limit N]
Example:
python scripts/find_skills.py "react performance"
python scripts/find_skills.py "docker" --limit 5
Output: JSON array of matching skills with name, source (owner/repo), installs count, and url (skills.sh link).
2. Install Skill — add_skill.py
Download a skill from GitHub and register it in Skill Compose.
python scripts/add_skill.py
Example:
python scripts/add_skill.py "vercel-labs/agent-skills@vercel-react-best-practices"
What it does:
- Parses the
owner/repo@skill-nameidentifier - Tries multiple GitHub paths to locate the skill (
skills//,/, root) - Downloads all skill files (SKILL.md, scripts/, references/, assets/)
- Saves to the local
skills/directory - Registers the skill in Skill Compose via the import-local API
- The skill is immediately available for use in Agent Presets
CRITICAL: Never Combine Questions with Tool Calls
When you ask the user a question or present results for them to review, your response MUST end with text only. Do NOT include any tool call (execute_code, bash, etc.) in the same response. The user needs a chance to read and reply. If you combine a question with a tool call, the tool executes immediately without waiting — this breaks the conversation flow.
WRONG (never do this): > "Should I install X?" + [execute_code: install X]
CORRECT (always do this): > Turn 1: "Should I install X?" (text only, no tool calls) > Turn 2: User says "yes" > Turn 3: [execute_code: install X]
How to Help Users Find and Install Skills
Each step below MUST be a separate conversation turn. Never combine steps.
Step 1: Understand the Need
Identify what domain and specific task the user needs help with.
Step 2: Search
Run find_skills.py with relevant keywords. Try multiple queries if the first doesn't yield good results. Even if the user names an exact skill, always search first to find the correct source/owner and verify it exists.
Step 3: Present Results and Ask
Show the user the found skills with:
- Skill name
- Source repository
- Install count (popularity indicator)
- skills.sh link for more details
Ask which skill(s) they want to install. End your response here — no tool calls.
Step 4: Confirm
When the user picks a skill, repeat back what you will install and ask for confirmation. This must be a text-only response with no tool calls. Wait for the user to reply.
Step 5: Install
Only after the user confirms in a separate message, run add_skill.py. Report the result.
Common Skill Categories
| Category | Example Queries | |----------|----------------| | Web Development | react, nextjs, vue, css, tailwind, html | | Testing | testing, jest, playwright, cypress | | DevOps | docker, kubernetes, ci-cd, terraform | | Documentation | docs, readme, markdown, api-docs | | Code Quality | lint, refactor, code-review, typescript | | Design | ui, design, figma, accessibility | | Data & ML | pandas, data-analysis, machine-learning | | Productivity | git, automation, workflow |
Tips for Effective Searches
- Use specific domain keywords: "react performance" instead of just "fast"
- Try alternative terms if first search yields few results: "testing" → "jest" → "playwright"
- Popular skill sources include:
vercel-labs/agent-skills,google-labs-code/stitch-skills - Check install counts — higher counts generally indicate more mature skills
When No Skills Are Found
- Acknowledge that no matching skill exists yet
- Offer to help the user directly with their task
- Suggest the user could create a custom skill for their use case using
skill-creator
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: dp-archive
- Source: dp-archive/archive
- License: Apache-2.0
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.