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local_lint_summary

Summarize lint, test, or CI output files by grouping errors per file with counts and priority order, using a local model to keep large logs out of Claude's context.

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 agrupado, no el contenido literal. Si ejecutaste un comando cuya salida es larga, vuélcala a un archivo y pasa 'path'.

Resume salida de linters/tests/CI con un modelo local, sin gastar contexto de Claude.

Pensada para logs largos y ruidosos (ESLint, clippy, pytest, tsc, CI). Pasa 'path' y el
archivo se lee del lado del servidor, de modo que el log completo NO entra al contexto de
Claude: solo vuelve un resumen agrupado por archivo con el conteo por tipo de error/regla y
lo más importante primero. Alternativamente pasa 'text'. Enruta al modelo mecánico (corto) o
al de contexto largo (largo) automáticamente.

Args:
    path: Ruta al archivo de salida de lint/tests (leído server-side). Usa esto o 'text'.
    text: Salida de lint/tests como texto.
    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?

No annotations provided, so the description carries full burden. It details that the file is read server-side (thus no context consumed), returns a grouped summary by file with error counts, and automatically routes to short or long context model. This is comprehensive behavioral disclosure.

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?

Well-structured with bold lead, use-case guidance, and parameter list. Some redundancy (e.g., 'Pensada para logs largos y ruidosos' echoes earlier point) makes it slightly less concise, but overall efficient.

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 tool with 0% schema coverage, no required params, and an output schema, the description fully covers purpose, usage, parameters, and behavior. It is complete and leaves no ambiguity for an AI agent.

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?

Schema coverage is 0%, but the description explains each parameter: 'path' (file path read server-side), 'text' (inline text alternative), and 'max_words' (summary length). This adds essential meaning beyond the bare schema names.

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 lint/test/CI output with a local model, saving Claude context. It explicitly distinguishes from reading the file directly (Read tool) and is tailored for large files.

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?

Provides explicit guidance on when to use: when file is large (>200 lines / >10 KB) and only a grouped summary is needed. Also advises to dump command output to a file and pass 'path' for long outputs, ensuring proper usage.

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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