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Read-only

Search the map for a term, case-insensitively, across four of its five parts: objects (name, description, field names and descriptions), findings (title, description, evidence and recommendation), processes (object type and step types) and metrics (name, description, formula, caveats). Relations are NOT searched — get_object lists the ones touching an object, and route finds the path between two. Returns matches with a snippet showing why each row matched, counts per kind — how many rows matched — and results with an id, title and url: pass the id to fetch for the full document. At most 50 documents come back, shared out across the kinds; when more matched, truncated says so and the counts say how many. On a map larger than one call reads, truncated is set too and truncated_note says the counts may be lower bounds.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations only declare readOnlyHint=true; the description adds case-insensitive matching, snippet returns, counts per kind, result id/title/url, the 50-document limit, and truncation semantics. This goes well beyond the structured data and fully discloses behavior.

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?

The description is long but every sentence earns its place: purpose, exclusions, return details, limits, and truncation are all relevant. It is front-loaded with scope and exclusions, making it easy to scan.

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

Completeness5/5

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

For a search tool with one parameter, no output schema, and a read-only annotation, the description covers return format, count semantics, limit, truncation, and edge cases. An agent can correctly invoke it and interpret results without additional documentation.

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

Parameters4/5

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

The schema provides no description for the 'query' parameter (0% coverage), so the description's mention that it is a case-insensitive search term adds essential meaning. It doesn't elaborate on syntax or accepted formats, but for a single free-text parameter this is adequate.

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 action (search the map), enumerates the exact four parts covered, explicitly excludes relations, and names alternatives (get_object, route). This distinguishes it clearly from sibling tools.

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

Usage Guidelines5/5

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

Directly states 'Relations are NOT searched' and points to get_object and route as the correct tools for that case, giving explicit when-not guidance. Also explains the 50-document cap and truncation behavior, clarifying expected results.

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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