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zxhwolfe-dev

AI Workstation Open Source Intelligence MCP Server

search_ai_projects

Read-onlyIdempotent

Find open-source AI projects from explicit requirements and verify their quality. Get transparent evidence and uncertainty boundaries to make informed choices.

Instructions

Find and verify open-source AI projects from explicit requirements.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
localeNoen
request_idNo
constraintsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

Annotations already establish read-only, idempotent, open-world behavior, so the safety profile is covered without description. The description adds the 'verify' behavior and the explicit-requirements scoping, but does not disclose what verification entails or any operational quirks.

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 a single, front-loaded sentence with no filler, and every phrase ('find', 'verify', 'explicit requirements') adds at least some meaning. It is efficient, though slightly under-specified for a tool with multiple parameters.

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?

Although the output schema and annotations carry significant context, the description omits parameter semantics, usage conditions, and relationship to sibling tools. For a 4-parameter search tool with 0% schema coverage, this is not enough for a confident selection or invocation.

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

Parameters1/5

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

Schema description coverage is 0% and the description does not define query, locale, constraints, or request_id. The phrase 'explicit requirements' may hint at query/constraints but does not explain their meaning or format, so the description fails to compensate for the schema's lack of descriptions.

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

Purpose4/5

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

The description states a specific action ('Find and verify') and a clear resource ('open-source AI projects'), and adds a scoping phrase ('from explicit requirements'). It does not explicitly distinguish this tool from browse_radar_projects or find_alternatives, but the search/verify framing makes the primary purpose clear.

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

Usage Guidelines2/5

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

There is no guidance about when to use search_ai_projects versus its siblings, no exclusions, and no stated alternatives. 'From explicit requirements' weakly implies a use case, but the agent is left to infer when this tool should be chosen.

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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