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local_summarize

Read-only

Summarize large files or text with a local model, keeping content out of Claude's context. Pass a file path or text to get a concise summary.

Instructions

PREFIERE esta tool en vez de leer el archivo con Read cuando el archivo es grande (>200 líneas / >10 KB) y solo necesitas un resumen, no el contenido literal.

Resume texto o el contenido de un archivo con un modelo local, sin gastar contexto de Claude.

Usa esto para resumir archivos/documentos grandes: pasa 'path' y el archivo se lee del lado
del servidor, de modo que el contenido completo NO entra al contexto de Claude (solo vuelve el
resumen corto). Alternativamente pasa 'text'. Enruta al modelo mecánico (entradas cortas) o al
modelo de contexto largo (documentos grandes) automáticamente.

Args:
    text: Texto a resumir (usa esto o 'path').
    path: Ruta a un archivo cuyo contenido se resume (leído server-side).
    max_words: Longitud máxima del resumen en palabras.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNo
textNo
max_wordsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations declare readOnlyHint=true, consistent with a non-destructive tool. The description adds significant transparency: it explains that the tool uses a local model, routes to short or long context automatically, and for 'path' reads the file server-side so full content doesn't enter Claude's context. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured with a strong opening recommendation, bulleted usage notes, and a parameter block in a consistent format. It is slightly verbose but every sentence adds value, and the Spanish wording is natural.

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?

Given the presence of an output schema (not shown but indicated), the description does not need to detail return values. It covers the two input modes, automatic routing, and the context-saving advantage. Missing details: error handling for invalid paths or very large files, but overall complete for a summarization tool.

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?

With schema description coverage at 0%, the description compensates by clearly explaining each parameter: 'text' and 'path' as alternatives, and 'max_words' controlling summary length. It also clarifies the behavioral difference between using 'path' (server-side read) vs 'text'. However, it lacks details on allowed file types or path constraints.

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 summarizes text or file content using a local model, and explicitly recommends it over reading large files, distinguishing it from a likely sibling tool (Read). The verb 'summarize' and resource ('text or file') are specific.

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

Usage Guidelines5/5

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

The description gives explicit when-to-use criteria: large files (>200 lines/>10 KB) when only a summary is needed, and when not to use: when literal content is required. It also contrasts with reading the file directly, providing clear usage context.

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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