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album_duration_report

Generates a runtime profile for an artist's studio albums—total length, track count, and longest track per album, ranked by duration—to identify their longest and shortest releases.

Instructions

Runtime profile for an artist's studio albums: total length, track count and longest track per album, ranked by runtime — find the epics and the EPs. Quota: 🔴 paginated walk + batched /albums lookups.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
artist_idYesSpotify artist ID, URI, or URL
max_albumsNoAlbums to scan. Default: 30
max_resultsNo
response_formatNo'concise' = human prose, 'detailed' = more fields in prose, 'json' = raw API objectconcise
Behavior3/5

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

With zero annotations, the description carries the full behavioral burden. The 'Quota: 🔴 paginated walk + batched /albums lookups' line is a genuinely useful disclosure of API call pattern and cost, which is rare and valuable. But it doesn't state that the operation is read-only, what happens for an artist with no studio albums, or how results are paginated/capped.

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?

Two sentences with the core output contract front-loaded; no wasted words. The 'epics and the EPs' phrase adds mnemonic value rather than fluff, and the quota line packs disproportionate operational information into one compact fragment.

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

Completeness3/5

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

The description covers purpose and cost well for a report-style tool, but with no annotations and no output schema it leaves gaps: the concrete return shape beyond the three summary fields, ranking direction (descending is only implied by 'epics'), edge cases, and max_results semantics. Adequate for basic tool selection, thin for confident invocation.

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 75%, and the schema already documents artist_id, max_albums, and response_format including defaults and enum meaning. The description's quota line implies cost scales with the walk but never ties it to max_albums or explains how max_results caps output; max_results is left undocumented in both schema and description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific scope — an artist's studio albums — and three concrete outputs (total length, track count, longest track) with a defined ordering (ranked by runtime). The verb is nominalized ('Runtime profile') rather than an explicit action verb, and it doesn't name its closest siblings like albums_runtime_batch or album_track_stats, so differentiation is implicit in the 'studio albums' scope rather than explicit.

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 'studio albums' scope implies exclusions (no singles, EPs, live albums, remixes), and the quota warning signals this is a heavy operation, hinting the agent should prefer lighter tools when appropriate. However, no sibling is named and no explicit when-to-use / when-not-to-use guidance is given, so routing decisions rely on 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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