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enrich_artist

Read-only

Retrieve sourced background on a single artist from MusicBrainz and Wikipedia to answer questions about history, members, origins, influences, or career, returning cited passages for grounded responses.

Instructions

Look up background on one artist in the user's library, from published sources.

Call this for any question about an artist's history, members, origins, influences or career. Pass the artist's name and the user's question. It returns the passages from MusicBrainz and Wikipedia that best match the question.

Answer only from these passages. If they do not contain the answer, tell the user your sources do not cover it, even if you believe you know. Never fill the gap from your own knowledge.

Cite every passage you use by its id in square brackets, such as [can-03], straight after the claim it supports. Never cite an id this tool did not return.

This tool knows nothing about the user's tracks. Use query_library for those.

Input Schema

NameRequiredDescriptionDefault
artistYes
questionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.9/5.0
Behavior5/5

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

Goes well beyond the readOnly/openWorld annotations by disclosing the data sources (MusicBrainz, Wikipedia), the grounding contract (answer only from returned passages, refuse otherwise), and the citation protocol required in the reply. These are response-shaping rules the annotations cannot convey.

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?

Front-loaded with purpose, then usage, then output contract, then sibling routing. Every sentence adds an actionable rule; nothing is redundant with the schema or annotations.

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?

No output schema exists, and the description supplies the return shape ('passages ... that best match the question') along with the id format used in citations. An agent has everything needed to call it and to post-process the result correctly.

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, and it does: 'artist' is clarified as the name and 'question' as the user's question, which implies phrasing the question in natural language rather than keywords. It stops short of format examples or naming conventions for the artist string.

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 and resource ('look up background on one artist ... from published sources') and names the sources. The final sentence explicitly separates it from query_library, so an agent can route without opening the schema.

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?

Gives an explicit trigger ('any question about an artist's history, members, origins, influences or career') and an explicit exclusion plus alternative ('This tool knows nothing about the user's tracks. Use query_library for those.'). Both when and when-not are covered.

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