search
This skill should be used when the user needs to search for information, find files,look up content online, or retrieve data without providing input files.Trigger phrases include:- "search for", "find", "look up", "research"- "search the web", "search online", "fetch from URL"- "search files", "scan codebase", "find in project", "grep for"- "get news from", "read hacker news", "check what's trending"Supports multiple search modes:- local: Search local filesystem using Glob, Grep, Read, Bash- ...
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Installation for Agentic Skill
View all platforms →skilz install memorysaver/looplia-core/searchskilz install memorysaver/looplia-core/search --agent opencodeskilz install memorysaver/looplia-core/search --agent codexskilz install memorysaver/looplia-core/search --agent geminiFirst time? Install Skilz: pip install skilz
Works with 14 AI coding assistants
Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...
Extract and copy to ~/.claude/skills/ then restart Claude Desktop
git clone https://github.com/memorysaver/looplia-corecp -r looplia-core/plugins/looplia-core/skills/search ~/.claude/skills/Need detailed installation help? Check our platform-specific guides:
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Agentic Skill Details
- Owner
- memorysaver (GitHub)
- Repository
- looplia-core
- Stars
- 3
- Type
- Technical
- Meta-Domain
- cloud infrastructure
- Primary Domain
- linux
- Market Score
- 76
Agent Skill Grade
C Score: 76/100 Click to see breakdown
Score Breakdown
Areas to Improve
- Missing TOC for 175-line file
- Speculative Future Providers section
- Redundant input-less explanation
Recommendations
- Address 1 high-severity issues first
- Add trigger phrases to description for discoverability
- Add table of contents for files over 100 lines
Graded: 2026-01-05
Developer Feedback
I took a look at your search skill and wanted to share some thoughts.
Links:
The TL;DR
You're at 76/100, solidly in C territory. This is based on Anthropic's best practices for Claude skills. Your strongest area is Spec Compliance (13/15) — the frontmatter and naming are tight. Weakest area is Progressive Disclosure Architecture (18/30) — you've got a 175-line file with no table of contents and some content that could be layered better.
What's Working Well
- Spec compliance is locked in — Valid YAML, correct hyphen-case naming, solid third-person description with specific trigger phrases covering local and web search scenarios.
- Clear 3-step workflow — The mission-based input model is straightforward, and your output schema is complete and usable.
- Strong trigger phrases — You nailed discoverability with phrases like "search locally", "web search", "find information" — Claude will know exactly when to call this.
- Concrete examples — Three mission examples help people understand how to use it, which bumped up the utility score.
The Big One: Missing Error Handling Guidance
This is your biggest miss. Your "Important Rules" section covers the happy path only — you've got nothing about handling empty results, rate limits, or failed searches. That's a high-severity gap because Claude needs to know how to handle failures gracefully.
Fix: Add an Error Handling section with specific schemas and retry logic. Something like:
## Error Handling
**Empty Results:** Return schema with `results: []` and `error: "No results found for [mission]"`
**Rate Limiting:** Retry logic for external providers (jina.ai, firecrawl)
**Malformed Mission:** Va...
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