Skip to main content
Glama

search_text

Search for text across the document body, footnotes, and comments with case-insensitive or regex matching. Returns matching paragraphs with identifiers and context.

Instructions

Search for text across the document body, footnotes, and comments.

Args: query: Text to search for (case-insensitive), or a regex pattern. regex: If true, treat query as a Python regular expression.

Returns matching paragraphs with their paraId, source part, and context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
regexNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries the burden. It discloses that the search is case-insensitive and supports regex. It does not mention read-only nature explicitly, but the action 'Search' implies it. The return format is described, which adds 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 concise, with a clear structure including Args and Returns sections. Every sentence adds value without redundancy.

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?

For a simple search tool with 2 parameters and an output schema (though not shown), the description covers the essential aspects. It could mention potential limitations (e.g., no pagination info), but it is sufficiently complete for an agent to use correctly.

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?

Schema coverage is 0%, but the description adds meaningful details: 'query' is described as case-insensitive text or regex pattern, and 'regex' boolean is explained. This compensates for the lack of schema descriptions.

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 verb 'Search' and the resource 'text across the document body, footnotes, and comments'. It distinguishes itself from sibling tools (e.g., get_paragraph, add_comment) by specifying the scope. The return values are also mentioned, which adds clarity.

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?

The description implies usage for searching text but does not provide explicit guidance on when to use it versus alternatives. No when-not or sibling differentiation is mentioned, which is a gap.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/SecurityRonin/docx-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server