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dedupe_playlist_plan

Scan any Spotify playlist for duplicate tracks, then view grouped positions and a keep-first/keep-last removal plan. Read-only analysis to review before committing changes.

Instructions

Census every duplicate uri in a playlist — groups, all positions, and the exact keep-first/keep-last removal plan — read-only (commit with dedupe_playlist_apply). Quota: 🟢 1–2 GETs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_resultsNoMax items to return (default: SPOTIFY_MCP_MAX_ITEMS env or 50)
playlist_idYesPlaylist to scan (ID or spotify:playlist: URI)
response_formatNo'concise' = human prose, 'detailed' = more fields in prose, 'json' = raw API objectconcise
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it delivers: it explicitly states the operation is read-only (so the agent knows it is non-mutating) and discloses the quota cost ('🟢 1–2 GETs'). This is precisely the operational context an agent needs that structured fields do not provide.

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 tight sentences with zero filler. The core purpose is front-loaded, output contents are compressed into a parenthetical list, and the read-only/commit-path/quota details each earn their place. Structured as a single scannable block.

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 tool with no output schema and no annotations, the description conveys the essential return contents (groups, positions, removal plan), safety profile (read-only), workflow (commit via apply), and cost (1–2 GETs). Minor gaps remain — behavior for playlists with no duplicates, how max_results interacts with result grouping, and the structural shape of the output — but nothing critical for correct 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 description coverage is 100%, so all three parameters (playlist_id, max_results, response_format) are already documented in the schema. The description adds no parameter-level detail beyond implying the output is a removal plan, which maps to response_format. The baseline 3 applies because the schema does the heavy lifting.

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 names a specific verb ('census'), a precise resource (duplicate URIs in a playlist), and the exact output contents (groups, all positions, keep-first/keep-last removal plan). This distinguishes it sharply from the sibling dedupe_playlist_apply, which is the commit counterpart. No ambiguity about what operation this performs.

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

Usage Guidelines4/5

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

The description makes the plan-then-commit workflow explicit: it is read-only and the agent should 'commit with dedupe_playlist_apply.' This gives clear when-to-use context for the plan/apply pair. It does not, however, contrast with other dedupe-related siblings like playlist_dedupe_advanced or find_duplicates_in_playlist, so exclusions are only partial.

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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