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Glama

get_skill

Retrieve the full content of any skill by name to access stored procedures or guidelines for AI agents.

Instructions

Devuelve el contenido de un skill por nombre (ej. 'mi-skill' o 'mi-skill.md').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are present, so the description carries the burden. It accurately states the operation (returns content) and demonstrates accepted name formats, but it does not disclose behavior on missing skills, extension normalization, or whether the operation is read-only beyond the verb 'Devuelve'.

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?

Single sentence, front-loaded with the action and resource, with useful examples. No filler.

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?

For a one-parameter getter with an output schema, the description is largely sufficient: it specifies the resource, the input format, and the returned content. It could add a pointer to list_skills for discovery or error behavior, but these are not critical for correct invocation.

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%, and the description compensates by explaining that 'name' accepts either 'mi-skill' or 'mi-skill.md'. This adds format flexibility beyond the bare schema, though it does not specify case sensitivity or resolution rules.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Devuelve') and resource ('contenido de un skill') and gives two accepted name formats. It clearly identifies the tool as a skill-content getter, though it does not explicitly contrast it with list_skills or read_file.

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

Usage Guidelines2/5

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

No explicit when-to-use or alternative guidance is provided. It implies use when you need a skill's content by name, but does not mention list_skills for discovery or read_file for arbitrary files, nor any exclusions.

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