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by a2br

search_in_files

Read-only

Find specific terms inside course files and pages. Get matching pages with snippets and direct read calls, so you only open relevant content.

Instructions

Full-text search inside course files (PDF slides, lecture notes, handouts, code) and pages.

Returns the best-matching pages with a snippet and the exact call to read them, so you can
read only the relevant pages instead of whole files. The first search in a course downloads
and indexes its files (can take a minute); later searches are instant.

Args:
    query: Words that must all appear on the same page, e.g. "big-step semantics".
    course: Limit to one course (recommended); by default searches all ongoing courses.
    max_results: How many matching pages to return.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
courseNo
max_resultsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the readOnlyHint and openWorldHint annotations, the description discloses meaningful behavioral details: the first search downloads and indexes files with a latency cost, later searches are instant, and query words must all appear on the same page. This adds real operational context without contradicting the annotations.

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 well-structured and front-loaded: the core behavior, return value, and cost are stated first, followed by concise parameter explanations. Every sentence carries information useful for selecting or invoking the tool, with no filler.

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 an output schema, the description covers all essential calling context: scope, result shape, indexing tradeoff, and parameter semantics. Nothing an agent needs to decide whether to call it or how to call it is missing.

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

Parameters5/5

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

Although the schema has 0% description coverage, the description fully compensates by explaining each parameter: query requires all words on the same page, course limits scope and defaults to all ongoing courses, and max_results controls the number of returned pages. It adds practical meaning and an example that the schema alone lacks.

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 is explicit and specific: it states a clear verb ('full-text search'), a concrete resource ('course files ... and pages'), and the key output (matching pages with a snippet and an exact call to read them). This clearly differentiates it from a generic 'search' tool and from reading whole files.

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 conveys when to use the tool by explaining that it lets the agent read only relevant pages instead of whole files, and recommends limiting to one course. It does not explicitly name alternative tools or state when not to use it, but the context is clear enough for an agent to route correctly.

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