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find_modules

Convert fuzzy phrases like 'execution plan' or 'browser api' into exact module IDs before calling any module-specific tool when an exact ID is missing.

Instructions

Turn a fuzzy phrase ('execution plan', 'browser api') into exact module ids. Use before any module-specific tool when the user did not give an exact id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
tenantNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
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 behavioral burden. It does disclose the core behavior (fuzzy/semantic matching rather than exact lookup) and the intended call ordering, but says nothing about whether zero, one, or many candidates are returned, how ambiguity is resolved, or what the tenant scoping implies.

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 short sentences, zero filler, with the core transformation stated first and the call-ordering rule second. Nothing can be cut without losing guidance.

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?

There is no output schema and no annotations, so the description is the only source of behavioral detail. For a discovery tool whose results feed other tools, the missing information about return shape (single id vs candidate list) and the undocumented tenant parameter leave the agent guessing about downstream usage.

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 0%, so the description must compensate. It meaningfully explains the `query` parameter's expected content (fuzzy natural-language phrases, with examples), which is more than the bare string type conveys, but the `tenant` parameter is left entirely unexplained in both schema and description.

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?

Specific verb (turn) plus resource (fuzzy phrase -> exact module ids), with two concrete examples ('execution plan', 'browser api') that remove ambiguity. It also positions itself against the module-specific siblings by declaring it runs before them, so an agent can separate it from module_risk, risk_scan, etc.

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?

Gives an explicit trigger ('before any module-specific tool') and an explicit exclusion ('when the user did not give an exact id'), which is real routing guidance. It stops short of naming a particular sibling as the follow-on target or stating what to do if the query is already exact, so it is clear context rather than full alternative selection.

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