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ANeuronI

skills.sh MCP Server

by ANeuronI

search_skills

Search skills.sh catalog by query to find relevant skills for your task.

Instructions

Search for skills on skills.sh by query term.

CRITICAL WORKFLOW FOR AI AGENTS:

  1. Parse user intent and generate 3-5 diverse keywords (e.g., for "scrape websites", use "web scraping", "puppeteer", "crawler").

  2. Call this tool multiple times with different keywords if the first results are poor.

  3. DO NOT recommend a skill immediately. You MUST use 'get_skill_details' on top candidates to check their install counts and platforms first.

  4. Recommend the top 1-3 skills and provide the npx install command.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results (default: 50)
queryYesSearch query term
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It implies a read operation ('search') but does not detail behavior such as pagination, result structure, or any limitations. The workflow guidance adds some context, but core behavioral traits are missing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with a clear lead sentence followed by bullet points. Every sentence serves a purpose, though the 'CRITICAL WORKFLOW' section makes it slightly longer than minimal but well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with two parameters and no output schema, the description covers purpose and usage well but lacks details about the return format or what to expect from results. It is adequate for basic usage but not fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so both parameters (query, limit) are documented in the schema. The description does not add extra meaning beyond the schema's descriptions, meeting the baseline for high coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it 'search[es] for skills on skills.sh by query term', providing a specific verb and resource. It distinguishes itself from sibling tools like get_skill_details and get_popular_skills by focusing on query-based search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit workflow steps, including generating multiple keywords, calling the tool multiple times, and using get_skill_details before recommending skills. It clearly contrasts with sibling tools by guiding when to use each.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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