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Biogod2020
by Biogod2020

Find in Web Page

find

Search a given webpage for an exact phrase and retrieve compact context snippets around each match, making it easy to verify occurrences without reading the full page.

Instructions

Find a literal phrase in a page and return compact context windows around matches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
patternYes
max_matchesNo
context_charsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
errorNo
statusYes
matchesNo
patternYes
source_idNo
total_matchesNo

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral disclosure burden. It does reveal key behavior: matching is literal rather than regex or semantic, and the response consists of compact context windows around matches. However, it does not mention case sensitivity, failure modes, page loading behavior, or limits, leaving notable gaps.

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?

A single sentence contains the core action, the matching mode, and the response shape with no redundant words. It is front-loaded and easy to parse.

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?

The description is adequate for a simple tool, and the output schema likely covers return values. But with no annotations and no parameter documentation, it lacks details about max_matches behavior, exact context window semantics, and when to prefer sibling tools. It is minimally sufficient but not fully complete.

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

Parameters2/5

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. It clarifies that 'pattern' is a literal phrase and 'context_chars' relates to compact context windows, but it does not explain 'max_matches', 'url', defaults, or the exact relationship between parameters and output. This is only partial compensation for the missing 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 states a specific verb and resource: finding a literal phrase in a page and returning compact context windows around matches. The word 'literal' helps distinguish it from the sibling 'search' tool, which implies broader or semantic search. This is a clear, specific purpose statement.

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: use this tool when an exact literal phrase is needed within a page. However, it does not explicitly say when not to use it or mention alternatives like 'search' or 'search_images'. The usage guidance is present only by implication.

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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