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playlist_staleness_report

Calculate playlist freshness using added_at dates, median item age, and 90-day additions, so stale playlists become easy to spot.

Instructions

Per-playlist staleness report: newest/oldest added_at, median item age and count added in the last 90 days — find playlists rotting in place. Quota: 1 + N reads (N = playlists scanned), page-capped.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNomedian_age
limitNoHow many playlists to scan. Default 50.
max_resultsNoMax items to return (default: SPOTIFY_MCP_MAX_ITEMS env or 50)
response_formatNo'concise' = human prose, 'detailed' = more fields in prose, 'json' = raw API objectconcise
per_playlist_capNoMax items paged per playlist. Default 500.
Behavior3/5

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

With no annotations, the description carries the behavioral disclosure burden. It usefully discloses quota cost ('1 + N reads') and that reads are page-capped. However, it does not state whether the operation is strictly read-only, what happens with large playlists, or how failures/rate limits behave.

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 tightly packed sentences lead with the core metrics and purpose, then add quota and paging constraints. No filler or redundant restating of the tool name.

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 report-style tool with no output schema, the description names its key output fields and cost model, which is enough for an agent to decide whether to invoke it. It falls slightly short on explaining return structure and comparing with sibling tools, but the quota note and metric list make it largely complete.

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 high (80%), so the schema already documents most parameters. The description adds useful context about paging and scanning cost, but it does not clarify individual parameter semantics beyond the schema, such as how sort interacts with the report or what response_format variants produce.

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 specifies a per-playlist report with concrete metrics (newest/oldest added_at, median item age, count added in last 90 days) and an explicit intent ('find playlists rotting in place'). This clearly distinguishes it from sibling tools like playlist_staleness_score or playlist_health_check.

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 description gives a clear context for use — detecting stale or rotting playlists — but does not explicitly say when to prefer this over related alternatives such as playlist_staleness_score, get_playlist_added_dates, or playlist_health_check. No exclusions or comparison guidance is provided.

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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