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album_representative_plan

Builds a deterministic album sampling plan: opener, midpoint, closer, longest track, ordered by original position with cumulative offsets, from a single API request.

Instructions

Builds a deterministic "sample this album" plan: opener, mid-point, closer and the longest track, ordered by original position with cumulative offsets, from the full album payload. Quota: 1 GET /albums/{id} (+1 paged tracks walk above 50 tracks).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
marketNoISO 3166-1 alpha-2 market code (e.g. 'US'); omit for 'from_token' behaviour
album_idYesSpotify ID, URI (spotify:...), or open.spotify.com URL — all resolve to the same entity
response_formatNo'concise' = human prose, 'detailed' = more fields in prose, 'json' = raw API objectconcise
Behavior4/5

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

With no annotations provided, the description carries the full burden and does substantial work: it discloses the deterministic nature, the exact selection algorithm, the ordering rule, and the API quota (1 GET /albums/{id}, +1 paged walk above 50 tracks). It does not explicitly state read-only status or error behavior, but 'builds a plan' strongly implies a pure computation with no side effects.

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 dense sentences with zero filler. The first sentence front-loads the core action and output composition; the second adds the quota. Every clause earns its place, and the algorithm is packed efficiently without losing readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a plan-building tool with no output schema and no annotations, the description covers the essential behavioral surface: determinism, selection criteria, ordering, and API cost. Missing are edge-case behavior (e.g., albums with fewer than four tracks) and explicit confirmation of no side effects, but the core information an agent needs to call it correctly is present.

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 description coverage is 100%, so the schema fully documents album_id, market, and response_format. The description adds marginal value by noting the operation consumes the 'full album payload', which clarifies how album_id is used internally, but this is lightweight context rather than substantive parameter semantics.

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 ('Builds'), resource ('album'), and a precisely defined output: opener, mid-point, closer, longest track, ordered by original position with cumulative offsets. This clearly distinguishes it from siblings like album_openers_report, album_track_stats, or front_to_back_plan without needing to inspect their schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase "sample this album" plan implies the use case (wanting a representative cross-section of an album), and the quota line conveys cost expectations. However, there is no explicit when-to-use guidance, no exclusions, and no named alternatives among the hundreds of siblings, leaving selection partially to inference.

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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