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artuntan

SkillHub MCP

by artuntan

search

Find AI tools, skills, agents, and MCP servers by text query, type, ecosystem, or tags. Access over 20,000 resources from the SkillHub database.

Instructions

Search the SkillHub database (20,000+ AI resources) by text query, type, ecosystem, or tags. Use this for targeted lookups when the user is looking for a specific tool, compares options, or wants to browse resources in a specific category.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoFilter by resource type
queryYesSearch query — tool name, technology, or keyword
ecosystemNoFilter by ecosystem
maxResultsNoMax results to return (default: 15)
Behavior2/5

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

No annotations are provided, so the description must cover behavioral traits. It does not mention read-only nature, rate limits, or behavior on empty results. The focus is on purpose, not behavior, leaving significant gaps for agent decision-making.

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

Conciseness5/5

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

Two sentences that are front-loaded with the action and scope. No fluff or redundancy.

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

Completeness2/5

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

No output schema exists, yet the description does not mention return format, pagination, or error handling. It also contains an inaccuracy about tags. For a 4-parameter search tool with no annotations, this is insufficient.

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

Parameters2/5

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

Schema coverage is 100%, so baseline is 3. However, the description claims filtering by 'tags' which is not a parameter in the schema, causing potential confusion. It adds little beyond the schema.

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 the verb 'Search' and the resource 'SkillHub database (20,000+ AI resources)' with specific filtering dimensions (text query, type, ecosystem, or tags). It also explains the usage scenarios (lookups, comparisons, browsing), distinguishing it from sibling tools like get_resource or recommend.

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

Usage Guidelines4/5

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

The description gives clear context for when to use the tool ('targeted lookups', 'compares options', 'browse resources in a specific category'). However, it does not explicitly mention when not to use it or provide alternatives, but the guidance is sufficient.

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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