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Glama

distill_skill

Gathers all brain sources, memories, and connection notes for a topic so an agent can draft and save a skill file; returns the material, not the finished skill.

Instructions

Junta todo lo que brain tiene sobre topic (fuentes, memoria, notas de conexiones) para que el agente redacte un skill a partir de esto y lo guarde con write_file en skills/.md. Esta tool NO escribe el skill sola — devuelve el material.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.1

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden, and it does disclose the single most important trait: it is non-mutating ('NO escribe el skill sola — devuelve el material'), preventing a false assumption that it creates the skill. It does not mention permissions/scope limits or rate behavior, but the return format is covered by the output schema.

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?

Two tightly packed sentences: the first front-loads what it gathers and the downstream workflow, the second delivers the critical non-writing caveat. 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 single-parameter aggregation tool with an output schema, the description covers the source scope, the intended workflow, and the key caveat; return values are described by the output schema, so nothing essential is missing.

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%, so the description must compensate. It gives `topic` concrete meaning by spelling out the three material classes it drives (fuentes, memoria, notas de conexiones), which goes beyond the bare string type in the schema.

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 (gather/aggregate) and resource (all material about `topic`: sources, memory, connection notes), plus the downstream purpose. It also explicitly distinguishes itself from the write siblings by declaring it does NOT write the skill, so an agent can tell it apart from write_file/save_url without opening any schema.

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 workflow is clear: call this to collect material, then the agent drafts the skill and persists it with write_file at skills/<topic-slug>.md. This routes the agent toward the correct downstream tool, though it stops short of explicit when-not-to-use or an alternative like search_knowledge/list_sources for narrower lookups.

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