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search_tools

Search 174 CRUD tools using a natural language query to find the one for your task. Returns matching tool names and schema fields, with optional category/operation filters.

Instructions

Search through 174 available SOR CRUD tools. Returns matching tools with their relevant schema fields based on your query. Use this to discover which tool to use for your task.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results to return
queryYesNatural language search query (e.g., "create user", "list tickets by status", "update organization billing")
categoryNoFilter by category (user, organization, project, ticket, etc.)
operationNoFilter by operation type
include_schemaNoInclude relevant schema fields in results

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It does state that the tool returns matching tools and relevant schema fields based on the query, which is the core behavior. However, it does not explain relevance ranking, result limits, or behavior when no matches are found—though these are partially inferable from the schema.

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 concise sentences with no filler. The first sentence states scope and return value, and the second provides the intended use case. Every word contributes to the agent's understanding.

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?

The tool is a relatively simple meta-search utility with no output schema, so the description must convey what results look like; it does so by saying it returns matching tools with relevant schema fields. It also communicates the size of the searchable space (174 tools) and the intended workflow. A small gap is that it does not describe the shape of the returned tool objects, but the core invocation context is sufficiently 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 the schema already documents all five parameters thoroughly. The description adds only a high-level statement that results are based on the query, which is useful but not necessary. Baseline 3 is appropriate since the schema does the heavy lifting.

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 uses a specific verb ('Search through') and a specific resource ('174 available SOR CRUD tools'), then states the output: matching tools with relevant schema fields. It clearly distinguishes itself from siblings by positioning itself as the discovery tool, while execute_tool and get_tool_schema serve execution and schema retrieval.

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 says 'Use this to discover which tool to use for your task,' which gives the agent a clear trigger condition. It does not explicitly name alternatives or say when not to use it, but the discovery framing is sufficient context given the sibling tool names.

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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