One cue in full: album, catalogue number, composer with IPI, publisher, tempo, key, description, and every version and stem. Takes a track_id OR the track's title — call it by name when the user names a cue.
| Name | Required | Description | Default |
|---|---|---|---|
| track_id | Yes | e.g. 'AIN-CAT 031_002' or 'Shine On Today' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations show readOnly, idempotent, non-destructive, so the descrption doesn't need to re-state that. It adds useful behavioral detail: 'Takes a track_id OR the track's title' and the fact that all versions and stems are returned. This goes beyond both the title and the bare schema, so it is valuable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, direct and front-loaded with the purpose. No wasted words; the phrase 'call it by name when the user says the cue' is a compact, valuable usage instruction.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has one parameter, 100% schema coverage, and annotations that establish the safety profile. With no output schema, the description spells out the exact return fields ('album, catalogue number, composer with IPI, publisher, tempo, key, description, and every version and stem'), so the agent knows what to expect. Nothing critical is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the schema itself already documents both accepted forms (id and title). The description adds a helpful rule of thumb ('call it by name when the user says the cue'), but most parameter meaning is already present in the schema. Hence baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'one cue in full', then enumerates the exact fields returned (album, catalogue number, composer, publisher, tempo, key, description, every version/stem). This clearly distinguishes it from sibling tools like search_by_reference or find_track, which are for locating tracks rather than getting all details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly says 'call it by name when the user names a cue', which tells the agent when to invoke this tool. It also expresses that it accepts a track_id OR title, providing a practical entry condition. It does not explicitly contrast with sibling search tools, but the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
search_music, find_soundtrack, and search_by_reference all discover catalogue music, and find_soundtrack overlaps with search_music for description-based requests. The long descriptions clarify the intended input type, but an agent could still reasonably pick the wrong tool when a user asks for music for a video.
Most tools follow a readable verb + object pattern (analyze_video, deliver_score, get_track, get_upload_link), but others are noun phrases (cue_sheet, listen_link, feedback) or awkwardly different (about_ainsof, score_my_video). The naming is not chaotic but lacks a single consistent convention.
With 12 tools, the set is within the well-scoped 3-15 range and each tool addresses a clear stage of the catalogue and scoring workflow: search, preview, upload, analyze, score, deliver, and feedback. No obvious filler or redundancy bloating the count.
The set covers the core lifecycle from music discovery and video analysis through scoring, delivery, and user feedback. Minor gaps exist such as no explicit browse/album listing tool, but search_music can retrieve albums and composers, so this should not cause agent failures.