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Find exact text

find_exact_text
Read-onlyIdempotent

Locate a literal string in the current corpus, optionally restricted to a document.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
documentNo
max_resultsNo
case_sensitiveNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • removedInput schema / properties / case_sensitive / description
      Removed value: -"Exact-case match (default False)."
    • removedInput schema / properties / document / description
      Removed value: -"Optional exact source file name to restrict the search."
    • removedInput schema / properties / max_results / description
      Removed value: -"Max (file, page) matches to return (1-50, default 20)."
    • removedInput schema / properties / text / description
      Removed value: -"The exact string to find (min 3 characters)."
  2. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds useful scoping context ('current corpus' and 'optionally restricted to a document') but does not disclose any other behavioral traits such as result ordering, limits, or error conditions. This is adequate given the strong annotation coverage.

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 a single, tightly phrased sentence that front-loads the core action and scope. Every word adds value, with no redundant or filler content. It is an example of concise, efficient writing.

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 simple with an output schema and strong annotations, so the description does not need to explain return values or safety. It covers the core behavior and scoping. The only missing element is explicit differentiation from the sibling 'search' tool, which is a minor gap and partly covered by the literal string phrase. Overall, the description is complete enough for correct invocation.

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 for undocumented parameters. It adds meaning to 'text' (literal string) and 'document' (restriction scope), but it does not explain 'max_results' or 'case_sensitive' beyond their self-explanatory names and schema defaults. The description provides partial value but not full compensation for the low schema coverage.

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 states a specific verb ('Locate'), a clear resource ('a literal string'), and scope ('in the current corpus, optionally restricted to a document'). The term 'literal string' effectively differentiates it from the sibling 'search' tool, which likely uses fuzzy or semantic matching. This makes the purpose unambiguous and distinct.

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

Usage Guidelines3/5

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

Usage guidance is only implied: the word 'literal' suggests using this tool for exact substring matching rather than a semantic search, but the description does not explicitly mention when to prefer it over the sibling 'search' tool or any other alternative. There is no mention of when not to use it. The agent must infer the selection criteria from the wording.

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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