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docs_install_docset

Idempotent

Downloads and indexes an offline documentation set by slug, enabling local API searches without internet. Runs as a background job and returns immediately.

Instructions

Download and index one offline docset in background (install docs, instalar documentación, descargar)

Takes a slug from docs_catalog (e.g. "python~3.13"). Reaches the internet. Runs as a background job and returns at once; follow it with docs_libraries (jobs) and search it with docs_search when done.

Args: slug: the exact slug from docs_catalog.

Returns: {job_id, status, slug, message}. Keywords: install docset, download documentation, offline docs, instalar documentacion, descargar documentacion

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false, openWorldHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds genuinely new context the annotations lack: it reaches the internet, runs asynchronously in the background, and returns immediately rather than blocking.

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 opening sentence is front-loaded with the scope and the sync/async behavior, and the Args/Returns blocks are compact. The bilingual keyword lines restate content already in the first sentence, which is mild padding but may aid retrieval.

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?

With no output schema, the description supplies the return shape {job_id, status, slug, message} and the async job-tracking workflow. An agent has everything needed to invoke it and know what to do next.

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% for the single 'slug' parameter, so the description must compensate. It does: the slug is defined as the exact identifier from docs_catalog with a concrete example ('python~3.13'), which is enough to call the tool correctly.

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?

States a specific verb+resource: 'Download and index one offline docset in background.' The word 'offline' plus 'background' distinguishes it from siblings like docs_index_folder and docs_catalog at a glance.

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?

Gives an explicit workflow: slug comes from docs_catalog, follow progress with docs_libraries (jobs), then search with docs_search. It names the prerequisite source and the follow-up tools, though it does not explicitly exclude docs_index_folder as an alternative.

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