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search_open_source_accelerators

Find maintained, commercially reusable open-source projects for a niche, with license posture. Use to avoid rebuilding infrastructure and to check whether a dependency is safe to ship.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
genreNoRestrict to one App Store category, e.g. Productivity.
limitNoMaximum number of results to return.
themeNoComplaint theme key, e.g. data_loss_sync, paywall_aggressive, ai_quality.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • changedInput schema / properties / genre / description
      Previous value: -"App Store category, e.g. Productivity."New value: +"Restrict to one App Store category, e.g. Productivity."
    • addedInput schema / properties / limit / description
      Added value: +"Maximum number of results to return."
    • addedInput schema / properties / limit / maximum
      Added value: +200
    • addedInput schema / required
      Added value: +[]
  2. First observed

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries full behavioral burden. It does reveal that results include 'license posture' and implies filtering for maintenance and commercial reusability. However, it does not state whether the tool is read-only, describe the return shape, or mention any limits, pagination, or error behavior. Adequate for a simple search tool but not thorough.

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 efficient sentences with no fluff: the first gives the action and scope, the second gives concrete use cases. Information is front-loaded and every clause earns its place.

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

Completeness4/5

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

For a simple tool with three optional parameters and no output schema, the description covers the core purpose and canonical usage scenarios. It omits details like exactly what 'license posture' means and how results are ordered, but these are minor given the schema already documents parameters.

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 the parameters are already fully documented in the schema (genre, limit, theme). The description adds nothing about how or when to use parameters, so the baseline score of 3 is appropriate.

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?

States a specific verb ('Find'), resource ('open-source projects'), and discriminating criteria ('maintained, commercially reusable', 'with license posture'). Also gives concrete use cases ('avoid rebuilding infrastructure', 'check whether a dependency is safe to ship'), which makes the tool's role clear and distinguishes it from sibling tools that focus on market analysis or app briefs.

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 explicitly states when to use the tool ('Use to avoid rebuilding infrastructure and to check whether a dependency is safe to ship'). It does not name alternatives or exclusions, but none of the listed siblings perform a similar function, so the missing when-not guidance is a minor gap.

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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