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document_search

Search for text within LibreOffice documents to find matching paragraphs, cells, or slides with surrounding context for efficient document analysis.

Instructions

Search for text within a document. Returns matching paragraphs/cells/slides with surrounding context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
docIdYesDocument handle returned by document_open
queryYesText to search for (case-insensitive)
limitNoMax results to return. Default: 10
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that the tool returns matching paragraphs/cells/slides with surrounding context, which is useful behavioral information. However, it doesn't mention important traits like whether it requires document_open first, performance characteristics, or error handling for invalid queries, leaving gaps in transparency.

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 perfectly concise with two sentences that directly state the tool's function and return value. Every word earns its place, and it's front-loaded with the core purpose. No unnecessary information or redundancy.

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?

Given no annotations and no output schema, the description provides basic purpose and return format but lacks details on behavioral traits, error conditions, or output structure. For a search tool with 3 parameters, this is minimally adequate but leaves significant gaps in understanding how to use it effectively.

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?

The schema description coverage is 100%, so the schema already fully documents all parameters. The description doesn't add any additional meaning beyond what's in the schema descriptions (e.g., it doesn't explain search algorithm details or context window size). Baseline 3 is appropriate when 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 clearly states the tool's purpose with a specific verb ('Search') and resource ('text within a document'), and distinguishes it from siblings by specifying it returns matching content with context, unlike document_read_text or document_read_range which read specific sections without search functionality.

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 implies usage context by mentioning it searches within a document and returns matches, suggesting it's for finding specific content rather than reading entire documents. However, it doesn't explicitly state when to use alternatives like document_read_text for direct reading or document_list for browsing documents, leaving some ambiguity.

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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