FreqBlog Music Metadata

Get Related Artists

get_related_artists

Read-only

Artists related to a seed artist — the drop-in for Spotify's removed GET /v1/artists/{id}/related-artists. No artist graph exists, so we derive one: build the seed artist's track-vector centroid, take its nearest catalogue tracks, aggregate by artist (each scored on its top-3 track similarities so a prolific artist can't dominate) plus a same-genre lift and a cross-genre penalty.

Returns `artist`, `count`, and `related` (each {artist_name, score, match_count,
sample_track_id}). Pass a sample_track_id straight to get_audio_features or
suggest_next_track. Costs 2 quota units.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Number of related artists to return (default 20).
`artist`	Yes	Seed artist name (as it appears in the catalog; case-insensitive).

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.4/5.0

Behavior5/5

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

Annotations already declare readOnlyHint and openWorldHint. The description adds substantial behavioral details: no exact graph exists, derivation via track vectors, scoring with same-genre lift and cross-genre penalty, and cost of 2 quota units. No contradictions.

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 description is well-structured with purpose first, then algorithm, return format, usage hints, and cost. It is somewhat lengthy but every sentence adds value. Slightly verbose for very concise standards, but still earns a high score.

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?

Given the algorithmic complexity and the presence of an output schema, the description fully covers purpose, return structure, invocation patterns (e.g., passing sample_track_id to other tools), and cost. No gaps identified for an agent to use the tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the schema already describes both parameters (artist and limit) adequately. The description does not add new meaning or constraints beyond the schema, so a baseline score of 3 is appropriate.

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 returns artists related to a seed artist, explicitly comparing it to Spotify's removed endpoint. It distinguishes itself from siblings by detailing its derived algorithm and naming specific use cases.

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 description positions the tool as a drop-in replacement for Spotify's related-artists endpoint, giving clear when-to-use context. It lacks explicit exclusions or comparisons to other sibling tools like get_recommendations, but the context is strong enough for an agent to decide.

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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TDQS

A4.6/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose: search, feature retrieval, set building, transition scoring, etc. There is no overlap or ambiguity.

Naming Consistency5/5

All tools use consistent snake_case verb_noun pattern (e.g., find_tracks_by_key, get_audio_features, build_setlist). No style mixing.

Tool Count5/5

12 tools is well within the ideal range, covering search, features, discovery, and set building without bloat or deficiency.

Completeness4/5

Core metadata retrieval, search, harmonic mixing, and DJ set tools are all present. Minor gaps like user library management are outside the scope.

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