FreqBlog Music Metadata

Tag Track

tag_track

Read-only

Get a compact, HONESTLY-LABELLED tag list for a track — energy / danceability / valence / acousticness / instrumentalness, plus a mood tag and a broad genre tag. It is a tag-shaped projection of the same open-data analysis get_audio_features returns (no audio upload, no extra compute), so it costs the same 1 quota unit, charged only on a served result.

The differentiator vs opaque taggers (e.g. Cyanite) is that EVERY tag carries its own
`confidence` and `provenance`:
  - confidence: measured (our Essentia analysis) | derived (MIREX mood from valence+energy) |
    model-estimated (AcousticBrainz mood SVM probability — research-grade, raw prob in `value`) |
    catalog-genre (broad catalogue tag, not fine-grained).
  - provenance: essentia | valence+energy | acousticbrainz | catalog.
`value` is the [0,1] score for numeric tags and null for label-only tags (mood category, genre).

Provide AT LEAST ONE identifier: `track` (optionally with `artist`), `isrc`, `mbid`,
`spotify_id`, or `track_id` (catalog itunes_track_id). If you know several, send them all —
they resolve by precedence (`track` > `isrc` > `track_id` > `mbid` > `spotify_id`) and the
rest are ignored, so you never have to pick. The broad, reliable coverage is the
MEASURED tags from our Essentia analysis over the analysed catalogue (plus on-demand by name);
MBID/ISRC additionally reach 7.5M+ AcousticBrainz recordings WHEN you supply that identifier.

Returns { track, count, tags:[{tag, category, value, confidence, provenance}], disclaimer }.
For the full numeric feature set use get_audio_features; for nearest tracks use a discovery tool.

Input Schema

TableJSON Schema

Name	Required	Description
`isrc`	No	ISRC, e.g. 'USUM71900001'.
`mbid`	No	MusicBrainz recording ID (UUID). Tags come from AcousticBrainz for that exact recording.
`track`	No	Track title. Use with `artist` when known. Supply AT LEAST ONE of track/isrc/mbid/spotify_id/track_id. Sending several is fine — they resolve by precedence (track > isrc > track_id > mbid > spotify_id).
`artist`	No	Artist name. Only used with `track`; improves accuracy.
`track_id`	No	Catalog itunes_track_id from a search_catalog or get_audio_features result.
`spotify_id`	No	Spotify track ID, 'spotify:track:...' URI, or open.spotify.com URL. Resolved from our Spotify-ID map or, on a miss, by matching the track's title — a title several artists share is ambiguous and misses rather than guessing; prefer track (+artist) or isrc.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A5/5.0

Behavior5/5

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

Annotations readOnlyHint=true and openWorldHint=true are corroborated and extended: the description adds quota cost, resolution precedence, 'misses rather than guessing' on ambiguous Spotify-ID title matches, and the provenance/confidence semantics of each tag. It explains coverage differences between Essentia and AcousticBrainz data without contradicting annotations.

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?

The description is long, but every section earns its place: purpose, differentiation, provenance semantics, identifier guidance, return shape, and alternatives. It is front-loaded with the core action and uses compact formatting for the confidence/provenance taxonomy.

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 6-parameter tool with an output schema, the description is complete: it states required input combinations, result shape, cost, coverage caveats, and how to get alternative outputs. An agent has everything needed to select identifiers and interpret tags.

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

Parameters5/5

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

Schema coverage is already 100%, and the description adds meaning beyond it: the precedence hierarchy track > isrc > track_id > mbid > spotify_id, the role of artist as an accuracy booster, the 7.5M+ AcousticBrainz coverage via MBID/ISRC, and the ambiguity behavior of spotify_id. This lets an agent choose identifiers 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?

Description opens with a precise verb and resource: 'Get a compact, HONESTLY-LABELLED tag list for a track' and enumerates the exact tag categories. It distinguishes itself from get_audio_features ('full numeric feature set') and 'a discovery tool', so an agent can tell it apart.

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?

Explicit routing guidance closes the description: 'For the full numeric feature set use get_audio_features; for nearest tracks use a discovery tool.' It also states the required input condition (AT LEAST ONE identifier), the precedence order, and when MBID/ISRC are advantageous.

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.

Resources

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