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

The only annotation is destructiveHint=false, so the safety profile is thin and the description carries most of the burden. It discloses the 100-URI ceiling, but says nothing about dedup defaults, ordering/position side effects on existing items, idempotency, or error behavior for invalid URIs. This is adequate but clearly short of full behavioral disclosure for a mutation tool.

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 short sentences, the action front-loaded and the limit immediately after. Nothing wasted and nothing buried.

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?

With five parameters, no output schema, and a mutation that can exceed a single-call limit, the description is thin: it omits how to handle more than 100 URIs, whether duplicates are skipped by default, and which sibling to use for bulk work. It is minimally viable but leaves a routing gap against batch_add_to_playlist.

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 already documents dry_run, position, check_duplicates, and the uris cap, so the baseline of 3 applies. The description's only parameter-relevant statement (max 100 URIs) duplicates maxItems: 100 in the schema, adding no meaning beyond it.

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?

States a specific verb (add) and resource (playlist) plus the item types accepted (tracks or episodes). It does not distinguish itself from the sibling batch_add_to_playlist, which appears to serve the same purpose at a different scale, leaving the agent to guess which to call.

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?

No when-to-use guidance, no exclusions, and no mention of alternatives such as batch_add_to_playlist, add_to_queue, or replace_playlist_items. The only hint is the 100-URI cap, which implies a bulk boundary but doesn't state how to route around it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations only declare destructiveHint=false, so the description carries most of the burden. 'To the end of the playback queue' usefully discloses append/ordering behavior, but it omits notable traits such as the need for an active playback device and the fact that this mutation is additive-but-persistent.

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?

A single well-formed sentence with the resource and the placement constraint front-loaded; every word earns its place.

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?

For a simple one-required-param tool with no output schema and full schema coverage, this is mostly adequate, but the device targeting (device_id) and the active-device precondition are never surfaced, leaving a real behavioral gap for an agent.

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%, so uri, dry_run, device_id, and response_format are all already documented in the schema, including the dry_run preview semantics and the response_format enum. The description adds nothing beyond the schema, so the baseline 3 applies.

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 gives a specific verb+resource ('Add a track or episode ... to the playback queue') and scopes it ('to the end'), which clearly separates it from play/pause/skip_next and get_queue siblings. It doesn't name an alternative explicitly, but the operation is unambiguous.

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?

Usage is only implied: 'to the end of the playback queue' hints at additive queuing versus immediate playback, but there is no explicit when-to-use/when-not clause and no sibling is named (e.g., play_from_search, play). An agent can infer intent but gets no routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With only destructiveHint: false in annotations, the description adds meaningful behavioral context: it discloses the multi-step order (resolve device hint, transfer playback, set volume/shuffle/repeat, start context) and that missing targets are skipped. It does not discuss auth needs, reversibility, or rate limits, but it goes beyond the annotation without contradicting it.

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?

The description is a single, front-loaded sentence that states the action and execution order without wasted words. Every clause earns its place by conveying the operation or its sequencing.

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?

For a multi-step mutation tool with no output schema, the description is largely sufficient: it covers the execution order and skip behavior for missing targets. It could mention dry-run behavior explicitly, but that is already fully documented in the input schema, so the remaining gap is minor.

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%, so all three parameters (name, dry_run, response_format) are already fully documented in the schema. The description adds no parameter-level detail beyond what is in the structured input schema, making the baseline of 3 appropriate.

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 ('Apply') and resource ('a saved scene') and immediately distinguishes the operation from siblings like save_scene, list_scenes, and delete_scene. It also spells out the execution sequence, making the tool's scope unambiguous.

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?

Usage is implied: the tool is for applying a saved scene, and the sequence is described. However, there is no explicit guidance on when to choose this over manually calling transfer_playback, set_volume, set_shuffle, set_repeat, or play, nor any exclusion criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations only supply destructiveHint=false, so the description must supply behavioral context, and it does: it walks every chapter page up to a shared fetch-all cap, reports scan coverage, and discloses the quota cost (1 audiobook GET + chapter page GETs). It does not state error/not-found behavior, which keeps it short of a 5.

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?

Three tight, front-loaded sentences with no filler; the output fields come first, then the scan behavior, then the quota cost. 'Shared fetch-all cap' is slightly jargon-y but informative.

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?

With no output schema, the description compensates by listing the returned metrics, and it covers the scanning/enumeration behavior and cost. Missing only edge-case behavior (e.g., audiobook not found) for a full 5.

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%, including the response_format enum, so the parameters are fully documented structurally. The description adds no additional parameter-level meaning beyond the quota note, so the baseline 3 applies.

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?

States a specific verb+resource (audiobook progress rollup) and enumerates the exact outputs: chapters total, played count, current chapter, percent complete. It is clearly distinguishable from all siblings, none of which report audiobook progress.

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?

The intent (fetch progress for an audiobook) is implied by the name and output list, but there is no explicit when-to-use or when-not-to-use guidance and no named alternative. Adequate but leaves routing to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations only provide destructiveHint=false; the description adds that the tool is read-only against Spotify, returns a snapshot file path and counts, and is intended as a pre-flight safety measure. This gives useful behavioral context beyond the annotation, though storage/retention details are not disclosed.

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?

Three short sentences with no filler. The action and purpose are front-loaded, and each sentence adds a distinct piece of information: what it does, what it returns, and that it is safe against Spotify.

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?

For a read-only snapshot tool with optional parameters and no output schema, the description gives enough to select and invoke it: purpose, usage timing, return shape, and safety. It could be more complete by clarifying what 'library' includes or how restore works, but that is not essential for calling this tool correctly.

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%, so the baseline is 3. The description does not add meaning beyond the schema for the two optional parameters; it only mentions return values generally, which is already implied by the tool's purpose.

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?

States a specific verb ('Create'), resource ('pre-flight library snapshot'), and purpose ('before a destructive operation'), which clearly distinguishes it from snapshot_playlist and backup_library. Also names the key return values (snapshot file path and counts), leaving no ambiguity about what the tool does.

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?

Explicitly says when to use this tool: before a destructive operation and for later restore. This provides clear context for choosing it, though it does not name alternatives or give exclusions, so it falls just short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint and idempotentHint, and the description adds substantive context beyond that: read-only against Spotify, the two cap env vars and the 'smaller wins' interaction, the backup directory default, and file mode 0600. It does not describe failure modes or partial-write behavior, keeping it short of a 5.

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?

Front-loads the essential fact (full-library snapshot to local JSON) and then packs the operational caveats into compact clauses. Dense but every clause carries information; the long cap sentence is slightly heavy but justified.

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?

With no output schema, the description usefully explains where files land, their mode, and the cap behavior, which covers what an agent needs to invoke and reason about the result. It stops short of describing the file's internal structure or how to locate a specific backup later.

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%, so all four parameters are already documented in the schema. The description reinforces the cap mechanics (walk_cap vs the env default, playlist cap interplay) but adds little that the schema does not already say. Baseline 3 is appropriate.

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?

States a specific verb (snapshot) and resource (entire library) plus the destination (local JSON file), and enumerates the categories captured. It does not explicitly contrast itself with siblings like export_library_json, export_all_playlists, or backup_first, so an agent must infer the distinction from the 'ENTIRE library' scope.

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?

The description implies when it applies (full-library snapshot) and gives operational context about caps and env vars, but never says when to choose it over export_library_json, backup_first, or export_all_playlists, nor when-not to use it. Usage is inferred rather than directed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations only supply destructiveHint=false, so the description carries most of the behavioral weight and delivers: in-batch and against-target dedupe, write batching in groups of 100, dry-run preview semantics, and an elicitation trigger at 100+ tracks. These are non-obvious operational traits an agent could not infer from the schema or annotations.

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?

Five compact sentences, each earning its place, with the core action front-loaded and operational caveats (dedupe, batching, dry-run, elicitation) following in descending priority. No filler.

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?

For a 9-parameter mutation with no output schema, the description covers the behaviors an agent most needs: dedupe semantics, batching, dry-run, and the confirmation threshold. It does not describe result shape or partial-failure behavior across batched writes, a minor gap since no output schema exists to cover it.

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%, so the schema already documents all nine parameters, setting the baseline at 3. The description echoes dedupe and target-selection semantics but adds no syntax or format detail beyond what the schema states, so it neither compensates for nor exceeds the structured data.

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?

States a specific verb and resource with scope: 'Add tracks from multiple source URIs (tracks, albums, artists, playlists) to a target playlist in one call.' The 'multiple source URIs ... in one call' framing distinguishes it cleanly from the single-item add_to_playlist sibling.

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?

Gives targeting guidance ('by ID/URI/URL or by lane name') and mentions dry-run and elicitation thresholds, which is useful context. However, it never explicitly states when to prefer this over add_to_playlist or how it relates to bulk siblings like merge_playlists or grow_playlist; the batch intent is only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations only include destructiveHint=false, which is minimal. The description discloses that it affects an in-process ramp and is conditional, but does not explain what happens to the ramp synchronization (e.g., devices return to original volume, whether any state is persisted) or any side effects beyond cancellation. Since annotations are sparse, the description carries more burden but still falls short of fully disclosing behavior.

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?

The description is one sentence, front-loaded with the action and resource, and immediately states the condition. Every word earns its place and there is no fluff.

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?

Given no output schema and minimal annotations, the description covers the essential purpose. It lacks details about scenarios (e.g., no ramp running), which might be handled by tool logic, but for a simple cancel operation it's sufficiently complete.

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%, so both parameters are documented in the schema. The description adds no extra semantics beyond what's in the schema; device_id's purpose is already clear. For a simple tool, this is acceptable, but it doesn't add nuance like whether omitting device_id cancels all ramps.

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 clearly states the action (cancel) and the resource (in-process wind-down ramp), and indicates the condition (if one is running). It differentiates from siblings like schedule_wind_down and wind_down_status, though it doesn't explicitly name them.

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?

The description implies when to use it (when a wind-down is running and you want to stop it) and the conditionality is clear. However, it doesn't explicitly contrast with alternatives like 'wind_down_status' for checking state or 'schedule_wind_down' for starting. There is no explicit when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already provide readOnlyHint and idempotentHint, so the description's added value is describing the output shape ('Rows carry {id, uri, follows}; returns a boolean per ID') and accepted URI formats. It does not mention auth or error behavior, but those are less critical for a read-only, idempotent check.

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 with zero fluff. The core purpose is front-loaded, then the distinction from check_in_library, then input formats, then output behavior, then a limit. Every phrase earns its place.

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?

For a simple read-only tool with a well-populated schema, the description covers purpose, input, output, and a key alternative. The only gap is that 'Max 50' is ambiguous (input ids vs output count) and max_results can exceed 50, but the schema clarifies ids maxItems=50 and max_results maximum=2000, so it's a minor ambiguity rather than a completeness failure.

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%, so the baseline is 3. The description adds no new parameter meaning beyond the schema – it only partially restates the ids parameter's accepted formats ('IDs or spotify:artist: URIs') which the schema already documents fully. max_results and response_format semantics are left entirely to the schema.

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 ('Check if the user follows specific artists') and explicitly distinguishes it from library-saved state by pointing to check_in_library. This clearly separates it from sibling tools like follow_artists, unfollow_artists, and check_playlist_following.

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 when not to use this tool ('this tests FOLLOW state, not library-saved state') and names the alternative tool (check_in_library). It also describes accepted input formats (IDs or URIs) and a practical limit, giving the agent enough to decide when to call it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint/idempotentHint, and the description adds substantial value on top: per-URI boolean return, the 40-URI cap, the unified endpoint, and the February 2026 API change that removed artist follow/unfollow. That last point is non-obvious behavioral context an agent could not infer from annotations or schema.

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?

Front-loads the decisive cue ('Preferred') and the capability in the first two sentences. The trailing explanation of the February 2026 following change is useful but somewhat discursive for a description.

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?

With no output schema, the description supplies the return shape (boolean per URI), the input ceiling, and the sibling routing. Nothing needed to invoke or interpret the tool 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 coverage is 100%, so all three parameters are already documented in the schema. The description restates the accepted URI types but adds no syntax or format detail for max_results or response_format, so the baseline 3 applies.

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?

States a specific verb+resource ('check whether items are saved in or followed by the user') and explicitly scopes it against the sibling check_following_artists. An agent can distinguish it from every other check_* / get_saved_* tool without opening a schema.

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?

Opens with 'Preferred' and says it accepts the widest URI mix in one request, then names the alternative (check_following_artists) and the exact condition that separates them (library-saved/followed state vs artist follow state). It also explains the one case where the alternative is no longer usable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare read-only/idempotent, and the description adds real behavioral context beyond them: batching mechanics (40/req, 1–2 GETs) and, importantly, the error semantics 'Unreadable state reports unknown, never not-followed' — a valuable non-obvious contract. Lacks any note on output shape, but the key edge-case behavior is disclosed.

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?

Dense and front-loaded: purpose first, then the operational detail and the safety guarantee. No padding; each clause carries information an agent needs.

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?

With no output schema, the description does explain the returned state (followed / unknown) and the batch size, which is enough for correct invocation. Minor gap: it does not describe what fields accompany each playlist in the result.

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 coverage is 100%, so the baseline is 3. The description reinforces the array bound ('1–50 playlists') but adds no format guidance for the ID/URI/URL items or the response_format enum beyond what the schema already documents.

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?

States a specific verb+resource: 'Check if you follow 1–50 playlists.' The scope (follow-state of playlists) is unambiguous and clearly distinct from the sibling check_following_artists, so an agent can select it without inspecting the schema.

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?

The batch size (1–50) implies the intended use, but there is no explicit when-to-use/when-not guidance and no named alternative (e.g., the artist counterpart or follow_playlist). Usage must be inferred from the operation itself.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations only declare destructiveHint=true, so the description usefully adds that the default is non-destructive, that the first occurrence of each duplicate group is preserved, and that bulk deletions require one confirmation. It could say more about irreversibility or whether an undo/receipt applies, but the safety-relevant behavior is well covered.

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?

Three tight sentences that front-load scope and default behavior before the mutation switch. The closing pointer to 'SPEC section 4' is an external dependency that costs a little self-containedness.

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?

With no output schema, the description does state what comes back (per-playlist findings, match_by echoed in results) and covers the confirmation flow for destructive runs. Complete enough for a library-wide cleanup tool, though return shape detail is thin.

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%, so each parameter is already documented in the schema. The description reinforces match_by semantics and the deprecation of apply, but adds no syntax or format detail the schema lacks. Baseline 3 is appropriate.

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?

Specific verb (scan/clean) plus resource (every playlist in your library) plus the object of interest (duplicate items), with the default behavior spelled out. It is clearly differentiated from single-playlist siblings like find_duplicates_in_playlist and remove_duplicate_playlist_items by the library-wide scope.

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?

States the default mode (report only) and the switch to mutation (apply=true), plus the confirmation gate for bulk removal. It does not explicitly name the single-playlist alternatives or say when a user should prefer them, so it falls short of a full when/when-not/alternative routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations only supply destructiveHint=true; the description adds substantial context beyond that: files are local and irrecoverable, preview-by-default, confirmation gating, SPOTIFY_MCP_CONFIRM=never bypass, age semantics based on mtimes, and that unrecognised files are listed rather than deleted.

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?

It is dense and front-loads the destructive action and target scope before the caveats, with each sentence carrying distinct information. It runs long, but almost no clause is redundant given the number of behavioral guarantees it must convey.

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?

No output schema exists, yet the description explains the PLAN/preview return, the listing of unrecognised files, and all safety gates. For a destructive file-deletion tool with zero required params, an agent has everything needed to call it correctly.

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 coverage is 100%, so the baseline is 3, but the description adds real meaning: ages are mtimes and the default retention window comes from SPOTIFY_MCP_BACKUP_ARTIFACT_RETENTION_DAYS (separate from the library window). It also clarifies that `files` overrides `family`/`older_than_days`, though the schema already states this.

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?

It states a precise verb (delete) plus the exact resource scope (NON-library backup artifacts), enumerating the three file families by glob pattern. It also explicitly distinguishes itself from sibling `delete_backup` and names the files that belong to that other tool.

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 gives explicit when-to-use routing (non-library artifacts vs. library backups via `delete_backup`), the safe default (preview), the commit path (dry_run=false, confirmation-gated), and refusal conditions (naming a library file, clients that cannot prompt). Alternatives and exclusions are both covered.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Adds genuinely useful context not present in the schema or the single destructiveHint annotation: the quota cost (GET images + PUT images, plus an image fetch). However it does not say whether the target's existing cover is overwritten or what happens on failure, so the mutation behavior stays partly opaque.

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 short sentences, purpose front-loaded ahead of the quota note; nothing is wasted. The parenthetical 'plus image fetch' is slightly cryptic but does not bloat the text.

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?

For a simple copy tool with a full-coverage schema and no output schema, the essentials are covered. The remaining gap is the effect on the target's existing cover and any failure/permission behavior, which an agent would want before invoking.

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%, including dry_run and image_index semantics, so the schema carries parameter meaning fully. The description adds nothing parameter-specific, making the baseline 3 appropriate.

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?

States a specific verb and resource: copy the cover image from a source playlist to a target playlist. It is inherently distinguishable from nearby siblings like get_playlist_cover and upload_playlist_cover, though it never names them or explicitly disambiguates.

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?

No when-to-use guidance and no alternatives referenced. The quota note is operational cost information, not routing guidance, so an agent still infers on its own when cloning a cover is preferred over uploading one.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already carry readOnlyHint and idempotentHint, so the safety profile is covered. The description adds genuine value beyond that by disclosing the cost ('Quota: 2 GETs') and the shape of the comparison (URL equality plus dimensions), which an agent cannot read off the annotations.

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 tight sentences, front-loaded with the action and resource, with the cost disclosure appended. Nothing is wasted and speed of scanning is high.

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?

With no output schema and six parameters, the description carries return-shape duty and does hint at it (URL equality, dimensions). It omits edge cases such as missing covers or mismatched sizes, but for a read-only comparison tool this is close to complete.

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%, so all six parameters (limit, scan_cap, playlist_a/b, max_results, response_format) are already documented in the schema. The description adds no parameter-level meaning beyond that, so the baseline 3 applies.

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?

States a specific verb and resource ('compare two playlists covers') and narrows the scope to URL equality and dimension checks, which separates it from one-cover tools like get_playlist_cover and clone_playlist_cover. It never names a sibling explicitly, so it stops short of a 5.

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?

There is no statement of when to reach for this versus get_playlist_cover or clone_playlist_cover, nor any precondition (e.g. both playlists must exist / have covers). The purpose is inferable but the selection guidance is absent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

The only annotation is destructiveHint=false, so the description carries the burden of behavioral disclosure. It adds valuable transparency by stating that the tool creates the new playlist first, adds tracks in batches of 100, and supports a dry-run mode that reports what would be created. It does not cover rate limits, auth requirements, or failure modes, but the core behavior is well disclosed.

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?

The description is three sentences with no filler. The first sentence states the purpose, the second explains the workflow, and the third covers the dry-run behavior. Every sentence earns its place and the key information is front-loaded.

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 10 parameters and no output schema, and the description explains the main workflow well. However, it does not cover return values, response formats, or edge cases such as the interaction between limit, scan_cap, and max_results. It is adequate for a basic understanding but leaves gaps for a complex tool.

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%, so the parameters are already fully documented. The description reinforces the 'batches of 100' behavior which relates to the limit parameter and mentions dry-run, but it does not add meaning beyond what the schema provides. Baseline 3 is appropriate.

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 clearly states the verb 'Duplicate' and the resource 'existing playlist' into a new playlist, and adds a meaningful detail: preserving track order. It is specific enough to understand the tool's core function, but it does not explicitly disambiguate from sibling tools like clone_playlist_live or playlist_clone_snapshot.

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?

No guidance is given on when to use this tool versus alternatives such as clone_playlist_live or playlist_clone_snapshot. The description implies usage for duplicating a playlist, but provides no exclusions, prerequisites, or distinguishing conditions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already indicate destructiveHint=false, so the description need not restate safety. It adds the dry_run preview behavior, which is a useful nuance. However, it doesn't disclose other behavioral aspects like required authentication, rate limits, or the result payload on success. Since the create operation is inherently mutating but safe, the description provides moderate additional context beyond annotations.

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 short sentences convey both the primary function and a key usage tip without any filler. The description is front-loaded with the core action and includes the dry_run hint efficiently.

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 is a simple create operation with five documented parameters, but there is no output schema and the description doesn't mention what the tool returns (e.g., the created playlist object). Given the complexity is low and the schema covers inputs, this is adequate but leaves the return behavior unspecified. No prerequisites or side effects are described beyond dry_run.

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%, so all five parameters are documented in the schema. The description mentions dry_run, which reinforces the schema's description but doesn't add new meaning. It doesn't clarify any parameter semantics beyond what's already in the schema, so the baseline score of 3 is appropriate.

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?

Description states a specific verb ('Create') and resource ('a new playlist for the current user'), which clearly distinguishes it from read-only or update operations. It is concise and unambiguous, though it does not explicitly contrast with sibling playlist tools.

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?

No guidance is given on when to prefer this tool over alternatives like update_playlist or add_to_playlist. The only usage hint is the dry_run flag for preview, but there is no explicit condition for when to use or avoid this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations only carry destructiveHint=false, which is thin. The description compensates by disclosing real behavioral traits: pool ceilings per source, truncation reporting, the fact that a capped pool is 'a floor, not a complete scan', and that dry_run creates nothing. It also warns about truncation for saved_tracks. The one small gap: it doesn't state what happens to an existing playlist of the same name, or whether this mutates user state (creation is implied). Still, this is well beyond the annotation floor, so a 4 is fair.

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?

The description is a single dense paragraph that front-loads the core purpose and then packs in constraints. It earns its sentences; every clause adds information. It could be split for readability, but there's no waste. Slightly long for a one-liner but appropriate for the tool's complexity (11 params, 3 sources). A 4 for tight content, minor ding for lack of visual structure.

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?

Given 11 parameters, 3 enum-based sources, no output schema, and sparse annotations, the description carries the full burden. It covers: what the tool creates, each source's behavior, pool ceilings, truncation, the dry_run preview, and the exclusion of deprecated endpoints. The parameter semantics dimension covers the rest. Nothing an agent needs to decide whether to call it or how to call it correctly 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 coverage is 100%, so the baseline is 3. The description adds meaning above the schema: it explains that limit applies 'after filters', clarifies that saved_tracks pool is the 'newest N saved tracks' with scan_cap defaulting to fetchAllCap=500, and defines source-specific pool ceilings. It also frames dry_run as 'previews the exact track list'. This is genuine added value beyond the property descriptions, so a 4.

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 ('Create') and resource ('a playlist from rules over your own listening data'), then enumerates the exact rule dimensions (source, artist filter, unique artists). It clearly differentiates from the many playlist-creation siblings (e.g. create_playlist, taste_to_playlist, playlist_template_apply) by anchoring on rule-based creation from personal listening data and explicitly ruling out deprecated recommendations endpoints. An agent can tell this apart from siblings without opening the schema.

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?

The description gives explicit 'when to use' context by naming the three data sources and their semantics, and it adds a crucial exclusion: 'No deprecated recommendations endpoints involved,' which tells the agent this is the modern replacement for a legacy flow. It also explains when dry_run is appropriate ('previews the exact track list without creating anything'). Combined with the sibling list (save_smart_playlist_rule, refresh_smart_playlist), an agent can select this over alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

The description goes well beyond the destructiveHint annotation, disclosing irreversibility, the sidecar deletion, confirmation-gating (dry_run default true, refusal when client can't prompt, SPOTIFY_MCP_CONFIRM=never bypasses), and path restrictions. This is rich, transparent behavioral context that an agent needs for a destructive operation. No contradiction with annotations.

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?

The description is five sentences, with the core action front-loaded in the first sentence. Every sentence adds value—sidecar deletion, irreversibility, confirmation gating, path restrictions—without redundancy. It's concise and efficiently structured for an agent to parse quickly.

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?

For a destructive tool, the description covers the critical aspects: what is deleted, irreversibility, confirmation steps, path safeguards. It does not describe the return format or error behavior for non-existent files, but for a mutation tool with a destructiveHint and full parameter documentation, the provided context is largely sufficient. A small gap remains around response/error details, hence 4.

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%, so parameters (file, dry_run, response_format) are already fully documented in the schema. The description adds no new parameter-level semantics beyond what's in the schema, and the schema entries are themselves descriptive (e.g., dry_run explains default and how to override). Baseline 3 is appropriate.

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 (Delete), resource (library backup file and its metadata sidecar), and scope (from SPOTIFY_MCP_BACKUP_DIR). It clearly differentiates from list/restore/backup creation tools by emphasizing irreversibility and the sidecar. This leaves no ambiguity about what the tool does.

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?

The purpose is clear enough that an agent would know when to use it (to delete a backup), but the description does not explicitly name alternative tools or provide conditional guidance like 'use this only when you intend permanent removal' or point to restoration tools for recovery. It focuses on behavior rather than decision context, so it falls short of strong usage guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

The annotations already declare destructiveHint=true, so the description's confirmation that this deletes a saved scene adds clarity about what is destroyed. It also specifies 'from the local sidecar', which is a useful behavioral detail not present in the annotations. There is no contradiction, and the description provides enough context for the destructive action.

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?

A single, front-loaded sentence with zero filler. Every word contributes to the meaning, and the structure immediately conveys the action and target. Nothing is wasted.

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?

For a simple two-parameter delete tool with destructive annotation and full schema coverage, the description is nearly sufficient. It clearly identifies the action, target, and storage location. The only minor gap is that it does not describe the return behavior or response_format effects, but that is partially covered by the schema and is not critical for a delete operation.

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%, with both 'name' and 'response_format' already documented. The tool description adds no additional meaning about the parameters or their relationships. This meets the baseline for schema-covered parameters but does not go beyond it.

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 uses the specific verb 'Delete' and clearly identifies the resource: 'a saved playback scene from the local sidecar'. This distinguishes it from siblings like delete_playback_bookmark and aligns with the scene-related tools (save_scene, list_scenes, apply_scene). The scope is unambiguous and immediately understandable.

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?

The description states the tool's function but provides no explicit guidance on when to use it versus alternatives such as delete_playback_bookmark or the other scene tools. Usage is implied by the name and resource, which is sufficient for a straightforward delete, but there is no stated exclusion or alternative routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already establish that this is a safe, repeatable read (readOnlyHint, idempotentHint), but the description adds real value beyond them: it discloses the source scan cap, that truncation metadata reports when source walks hit scan_cap, and that rendered rows are bounded by max_results. It stops short of describing output shape or how position comparison is computed.

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 tightly packed sentences, front-loaded with the operation and its result categories, followed by the capping/truncation semantics. No filler, restatement of the name, or redundant prose.

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?

For a comparison tool with no output schema and a fully documented parameter set, the description covers result categories, capping behavior, and truncation reporting, which is close to sufficient. It omits any note on empty/error cases or the fact that no parameters are required, but nothing critical to calling it correctly 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?

With 100% schema coverage the baseline is 3, but the description clarifies the non-obvious interplay between two similarly named caps: scan_cap bounds the source walk while max_results bounds rendered rows. That distinction is not obvious from the schema alone and materially helps correct invocation.

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?

States a specific verb and resource ('Compare two playlists') and enumerates the three result classes (only in A, only in B by track ID, in both but at different positions), which is genuinely informative. However, it never distinguishes itself from the many closely related siblings such as playlist_symmetric_difference, overlap_playlists, or playlist_union, so an agent must infer which comparison tool to pick.

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?

There is no when-to-use guidance, no prerequisites, and no named alternative despite a dense field of overlapping comparison/union/subtract/symmetric-difference siblings. Usage is only implied by the behavioral description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Goes well beyond the lone destructiveHint=false annotation: it discloses the sampling path vs. static-map fallback, that no Spotify endpoint is called, that nothing is mutated, and the exact failure contract (isError after one retry, never a guess). This is rich, high-value behavioral disclosure.

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?

Four front-loaded sentences, each carrying distinct information (purpose, execution path, side-effect profile, error semantics). Slightly dense but no wasted text.

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?

With no output schema and a rich response_format parameter, the description carries the return-value burden and does describe the output fields. A brief note on which format actually gets returned on the static-map path would close the last gap.

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 coverage is 100%, so mood, max_tokens and response_format are fully documented in the schema. The description adds the output vocabulary but no parameter-specific semantics beyond the schema, making the baseline 3 appropriate.

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?

States a specific verb and resource ('Turn a free-text listening mood into search terms') and enumerates the output shape (genres, keywords, terms to avoid). This is a unique utility with no equivalent among the siblings, so it is trivially distinguishable.

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?

The phrase 'for search' implies it is a pre-step to searching, but the description never states when to use this versus calling search/search_deep directly, nor any exclusions. Usage is implied rather than directed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

destructiveHint=false is already in annotations, and the description adds meaningful behavioral detail with the quota formula: GET /me/playlists + N×GET /playlists/{id}/items, capped by fetchAllCap. This helps the agent reason about cost and batch size, though auth requirements and sidecar-file naming are not disclosed.

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 short, dense sentences front-load the core action and then add the quota constraint without any filler or repetition. Every sentence earns its place.

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?

Given five fully documented parameters, the description covers the operation, scope choice, output format, output directory, and quota behavior. Minor ambiguity remains around the exact meaning of 'all' and the shape of the returned result, but with no output schema and strong parameter docs this is a minor gap.

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?

The input schema has 100% description coverage: all five parameters already carry descriptions, defaults, and enums. The description adds tool-level context like sidecar output and quota, but does not materially refine individual parameter meaning beyond what the schema already provides.

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 phrase 'Export every owned (or all) playlist with metadata + items to a sidecar file' names a specific verb, resource, and scope. The qualifier 'every' and the sidecar-file output clearly distinguish it from singular or JSON-specific export siblings, even though no sibling is named.

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?

The description gives clear context for the intended use case: bulk export of owned/all playlists, with scope selectable via the schema. It stops short of explicitly naming alternatives like export_playlist or sidecar_export_bundle or stating when not to use this tool, so the routing is left partly to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations provide only destructiveHint: false, so the description carries the behavioral burden. It discloses the file-writing side effect ('to a local directory'), the output field set, and — most valuably — that exported_at is the export time, not a follow date, because Spotify does not expose followed_at. This preempts a likely misinterpretation of the produced data, and none of it contradicts the annotations.

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?

Three sentences with the core purpose front-loaded in the first sentence and zero wasted words. The field list and the exported_at caveat each earn their place; the caveat preempts a data-interpretation error rather than padding.

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?

For a low-complexity tool (3 optional params, no output schema, non-destructive), the description plus schema cover purpose, destination, response mode (via response_format), field semantics, and the exported_at caveat. Minor gaps remain around overwrite behavior and directory creation, but nothing an agent needs to invoke the tool correctly 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%: all three parameters (format, output_dir, response_format) are documented with defaults, enums, and meaning, so the baseline is 3. The description adds marginal value by enumerating the exported fields (uri, name, genres), which clarifies what the chosen format will contain, but it doesn't deepen the meaning of any individual parameter.

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 uses a specific verb ('Export'), names the exact resource ('your followed artists'), the destination ('a local directory'), formats (JSON or CSV), and even the exported fields. Among the large sibling set of export_* tools, this uniquely targets followed artists, and it is clearly distinguishable from get_followed_artists by the explicit file-persistence behavior.

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?

Usage is only implied: the phrasing signals it is for creating a local file of followed artists. There is no explicit when/when-not guidance, and with retrieval siblings like get_followed_artists and broader exports like export_library_json in the sibling set, an agent gets no direct routing help. The exported_at caveat is informative but not usage guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations only include destructiveHint=false, so the description carries the burden of behavioral disclosure. It explicitly discloses the SPOTIFY_MCP_FETCH_ALL_CAP behavior, reporting cap_reached, truncated, and a prose footer, which is valuable context beyond the annotation. However, it does not mention whether existing files are overwritten or how the output directory is created, but those are minor gaps given the export action is clear.

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?

The description is two concise sentences that front-load the core purpose and then add the cap behavior. Every word earns its place, with no redundancy or fluff. It efficiently conveys the tool's function and a key edge case without extra text.

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 description covers the main export scope and the cap/truncation behavior, and the schema covers format and output details. However, it does not describe the return value for a successful export (only the cap case), and it omits details like whether the output directory is created automatically. Given the tool's complexity and lack of output schema, these are minor but notable gaps.

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?

The schema already provides full descriptions for all three parameters (format, output_dir, response_format), including enums and defaults. The description adds no additional parameter-level meaning beyond what the schema covers. Since schema coverage is 100%, a baseline of 3 is appropriate; the description's cap explanation is not parameter-specific.

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 clearly states the tool exports the full library (saved tracks, albums, shows, episodes, audiobooks) to a local directory in JSON or CSV format, with a specific verb and resource. It also mentions the cap behavior, which distinguishes it from other export tools. The scope is explicit, making it easy to differentiate from siblings like export_playlist or export_followed_artists.

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?

The description provides no guidance on when to use this tool versus the many other export tools in the sibling list (e.g., export_all_playlists, export_followed_artists, export_profile_state). It does not mention alternatives or exclusions, leaving the agent to infer usage context. No when-not-to-use conditions are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Beyond annotations (non-destructive only), it discloses real behavioral details: it writes a file with 0600 permissions, respects SPOTIFY_MCP_FETCH_ALL_CAP, uses before-cursor pagination, and reports path plus counts. It does not fully spell out overwrite/append or error behavior, so not a 5, but it goes well beyond the annotation.

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 with no filler; the operation, target, mechanism, environment constraint, and result are all front-loaded and compact.

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?

With no output schema and only a destructiveHint annotation, the description usefully states output (path + counts), file permissions, and cap behavior. The parameter details are already in the schema, and the description fills enough operational context; a brief return-format/overwrite note would make it fully complete.

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 coverage is 100%, so the baseline is 3. The description adds cross-cutting meaning that the schema lacks: the overall cap, pagination model, sidecar file behavior, and permission mode, which helps an agent understand how max_items/limit and before interact.

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 names a specific operation—exporting listening history (recently played) to JSON or CSV—and adds the API endpoint and pagination strategy, so the tool's job is clear. It does not explicitly differentiate itself from the similar sibling listening_history_export or other export_* tools, which keeps it from a 5.

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 implies when to use it (whenever a file-based export of recently played items is needed) and clarifies the pagination/fetch-cap behavior, but it never states when to prefer a sibling such as get_recently_played or listening_history_export, nor does it give exclusions. This is adequate but leaves routing to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

It adds genuinely useful behavioral detail beyond the annotations: internal pagination, mode 0600, output-root sandboxing, inline-vs-file behavior, and formula-safe CSV. However, the claim of a 'full item list' conflicts with the schema's max_results default of 50, so the transparency is incomplete and potentially misleading.

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?

Three dense sentences with the purpose front-loaded and no filler. Each sentence carries a distinct, useful fact: output formats, file-vs-inline behavior, and CSV security.

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 schema fills in most parameter detail and the description covers output modes well, but the description would mislead an agent about default truncation unless max_results is raised, and it does not mention sibling export formats. For a 7-parameter tool with no output schema, these are notable gaps.

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 coverage is 100%, so the baseline is 3; the description adds value on top by explaining output_path semantics (mode 0600, relative to the output root, inline when omitted) and CSV cell safety. Repeating the other parameters would be redundant.

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 opens with a specific verb and resource: exporting a playlist's full item list to M3U or CSV. It is clearly distinct from a generic get/list tool, but it does not explicitly differentiate itself from sibling exports like export_playlist_json, export_playlist_markdown, or export_all_playlists.

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?

The description gives clear guidance on choosing between file output and inline return ('pass output_path... or omit it') and explains the output root and file mode. It stops short of naming when not to use this tool, such as pointing agents to JSON or Markdown export siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations only provide destructiveHint=false, so the description carries the burden of explaining behavior. It adds that the output is a single schema-versioned JSON archive and specifies the artist-watchlist location, which is useful. However, it does not disclose overwrite behavior, directory creation, or whether the operation has any side effects beyond writing the archive.

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 with no filler: the first states the core action and content scope, the second adds a useful file-path detail. Information is front-loaded and every sentence earns its place.

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?

Given the simple export operation, well-documented parameters, and clear content enumeration, the description is nearly complete for correct invocation. It does not describe the return value or file-naming behavior, but no output schema exists and the operation's intent is clear enough.

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%, so the parameters (output_dir, include_history, response_format) are already fully documented. The description adds no parameter-level meaning beyond the schema, making the baseline 3 appropriate.

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 uses a specific verb and resource: 'export local sidecar stores' to 'a single schema-versioned JSON archive', and enumerates exactly which stores are included (scenes, genre-tags, playback-ext, search-history, mutations, artist-watchlist). This clearly distinguishes it from export siblings like export_library_json or export_listening_history without needing to open the schema.

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?

The description implies the tool is for backing up or migrating local profile/sidecar state, but it never explicitly states when to use this tool over alternatives. With several nearby export tools (sidecar_export_bundle, export_library_json, mutation_log_export), the lack of exclusion or alternative guidance leaves some ambiguity.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint and idempotentHint, so the description's 'Read-only' line is redundant but not contradictory. It does add genuine beyond-annotation context: the tag match is case-insensitive and resolved against 'your sidecar' (a local data source), which tells the agent the filtering semantics differ from a live API query. It stops short of covering result limits or error behavior, but the annotation baseline is already met.

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 tight sentences with zero filler, front-loading what is returned (URIs) and where they can be used before the read-only note. Every clause earns its place.

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?

With no output schema present, the description usefully explains the return value (URIs) and its downstream use, which the agent needs. It omits mention of the max_results cap behavior and result ordering, but for a filtered-list tool the essentials are covered.

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%, so the schema already documents kind, genre, max_results, and response_format including enums and the env-var default. The description only reinforces the case-insensitive genre matching already noted in the schema, adding little beyond it. Baseline 3 applies when the schema carries the full burden.

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?

States a specific verb and resource ('List URIs of your saved tracks or albums') plus the filtering criterion (artists carrying a genre tag). The scope is narrow and clearly distinct from siblings like search_saved_tracks or library_genre_report, and it even names what the output feeds into (create_playlist / add_to_playlist).

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?

The description implies usage by noting the output is 'directly usable as create_playlist / add_to_playlist input', which hints at a build-a-playlist workflow. However, it never states when to prefer this over alternatives such as search_saved_tracks or library_genre_report, leaving the routing decision to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Goes well beyond the readOnly/idempotent annotations by disclosing the exact-match criteria (same non-null ISRC and album id, duration ±2s, keeps oldest dated save), that near-duplicates are review-only with no removals, that undated saves sort last, and that it never mutates the library.

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?

Front-loads the core purpose and then layers matching semantics efficiently; every sentence carries information. A few sentences are dense and could be tighter, but there is no filler.

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?

With no output schema, the description carries the burden of explaining what comes back, and it does describe group types, exact vs. near distinction, and undated-save ordering. It stops short of describing the concise/detailed/json return shapes in depth, leaving a small gap.

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 coverage is 100%, so the baseline is 3, but the description adds genuine meaning: playlist_id denotes cross-referencing group members against a playlist for cleanup decisions, and include_near_duplicates is framed as an opt-in review-only mode. These enrich the parameters beyond their schema text.

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?

States a specific verb and resource: 'Read-only duplicate detection over your saved (liked) tracks.' The 'saved (liked) tracks' scope cleanly distinguishes it from sibling playlist duplicate tools like find_duplicates_in_playlist and find_duplicate_tracks_across_playlists.

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?

Gives clear conditions for the two modes (exact groups vs. opt-in near duplicates) and explains the optional playlist_id cross-reference use case. It never explicitly names an alternative sibling or states when NOT to use it, so it stops short of full routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds that the applied rule is echoed back as `match_by` so a group count is never unattributable, plus a pointer to SPEC section 4 vocabulary — useful context beyond the annotations, though nothing about result shape or limits.

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?

Front-loaded with purpose, then rules; two sentences carry real information. The echo-of-`match_by` point is stated twice (once in prose, once in the schema description), a small redundancy that keeps it from being maximally tight.

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?

With no output schema, the description does supply the key return-context detail (rule echoed in the result) and the matching-rule semantics. It omits result shape beyond group counts and limit behavior, but is otherwise sufficient for calling the tool correctly.

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 coverage is 100%, so the schema already documents all four parameters including the enum semantics and the default. The description largely restates the `match_by` rules and its echo behavior, adding marginal value over the structured field, which is the expected baseline when the schema does the work.

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?

Specific verb (find) plus resource (duplicate tracks) and an explicit scope ('in a playlist'), which separates it from siblings like find_duplicate_tracks_across_playlists and remove_duplicate_playlist_items. An agent can classify it without opening the schema.

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 clearly explains which matching rule each `match_by` value selects and the real-world cases they catch (relinks, remasters), which is genuine usage guidance. It does not, however, explicitly route the agent away from the removal/clone siblings, so it stops short of the top mark.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint and idempotentHint, so safety is covered. The description adds the API-quota behavior (one GET per playlist, N total), which annotations do not convey, but it says nothing about how duplicates are reported, ordering, or truncation with max_results.

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 short sentences, zero filler, with the scope definition and the quota cost front-loaded. Every clause earns its place.

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?

For a read-only, idempotent tool with three fully documented parameters and no output schema, the definition covers purpose and cost adequately. It could be slightly richer about what a duplicate match looks like, but nothing essential to invoking it 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%: the playlist ID formats, the 2-20 bound, the max_results default, and the response_format enum are all documented in the schema. The description adds no syntax or semantic detail beyond that, so the baseline 3 applies.

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?

States a specific verb (find) and resource (tracks) plus the exact scope qualifier 'appear in more than one of the given playlists (cross-playlist dupes)'. The parenthetical explicitly disambiguates it from the within-playlist sibling find_duplicates_in_playlist/remove_duplicate_playlist_items without opening a schema.

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 gives cost guidance (N GETs, one per playlist), which is genuinely useful, but never states when to prefer this over sibling overlap tools such as overlap_playlists, playlist_symmetric_difference, or playlist_union. Usage is implied by the purpose line rather than explicitly routed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so safety and repeatability are covered by structured data. The description adds useful operational context — the registry is live, 500+ tools, and the discovery set is always available via catalog — but discloses nothing about result ordering, match behavior beyond 'case-insensitive substring', or limits. Adequate but not rich.

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, zero padding, with the core purpose front-loaded before the routing advice. The parenthetical about the discovery set is terse but earns its place by telling the agent these tools remain callable.

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?

With annotations covering safety, an output schema covering return values, and full parameter documentation in the schema, the description only needed to supply purpose and routing — both delivered. Nothing an agent needs to invoke this correctly 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% with 3 parameters, each documented (query semantics, limit default/max, response_format enum meanings). The description adds no parameter guidance beyond the schema, so the baseline 3 is correct.

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?

States a specific verb (search) and resource (live tool registry) with the matching mechanism (name or description substring). It also quantifies scope (500+ tools), which lets an agent distinguish it immediately from the domain-specific search_* siblings that search Spotify content rather than the tool registry.

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?

Explicitly says to use it first when unsure which verb applies, gives a concrete example of the ambiguity it resolves (playlist vs snapshot vs search), and names the sibling discovery tools (inspect_tool, toolset_report) plus the catalog as alternate access paths. Both the when and the alternatives are stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations only supply destructiveHint=false, so the description must carry behavioral weight. It does add one useful operational fact — the quota applies to the paged GET /me/playlists endpoint — which hints at rate-limit and pagination costs. It says nothing about whether results are cached, how large the fetch can be, or how long it takes.

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 compact clauses with no filler, and the core inventory content is front-loaded before the quota note. The telegraphic list style ('counts, collab, public, follower totals') is dense but readable.

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?

With no output schema, the description carries the return-value burden; it does list the reported dimensions, which is helpful. However it leaves the shape of the audit output, whether it covers owned playlists in the same call, and the effect of the response_format parameter unstated.

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%, so max_results, only_followed, and response_format are fully documented in the schema; the description adds essentially nothing parameter-specific. Baseline 3 applies when the schema does all the work.

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 names a specific resource (followed vs owned playlists) and enumerates what the audit reports: counts, collaborator status, public/private, and follower totals. This distinguishes it from siblings like get_user_playlists and following_analytics, though it never names those alternatives explicitly.

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?

No statement of when to use this tool versus get_user_playlists, get_user_playlists_by_id, or following_analytics, all of which overlap on playlist surface area. The word 'audit' and the followed/owned comparison imply a reporting use case, but the agent must infer it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With only destructiveHint=false in annotations, the description carries real behavioral weight: it discloses the tag-sidecar data source, that popularity/followers are structurally unavailable (Spotify API change), and that a GET /me/following quota applies. These are non-obvious constraints an agent cannot infer from the schema. It stops short of 5 only because it doesn't say what happens when the sidecar is empty or stale.

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 tightly packed sentences with the data-source caveat front-loaded before the quota note. No filler, though the 'Quota: GET /me/following' fragment is cryptic enough that its brevity borders on ambiguity.

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?

For a read-only rollup with no output schema, the description covers the data-source and availability caveats but never indicates the shape or grouping of results, nor how top_n interacts with max_results. Adequate but with a noticeable gap for an analytics tool.

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%, so the schema already documents all four parameters including the 'unavailable' behavior for popularity/followers. The description's note about unavailable fields is largely redundant with the enum description, so it adds little beyond the baseline.

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?

States a specific resource and operation ('followed-artist rollups') plus the data source ('tag sidecar'), which is enough to distinguish it from get_followed_artists/check_following_artists. It does not explicitly name those siblings as alternatives, so it stops short of a 5.

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?

There is no explicit when-to-use guidance or routing against the many neighboring following/export tools. The quota note hints at cost but never tells the agent when this rollup is the right call versus get_followed_artists or export_followed_artists.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With only destructiveHint: false in annotations, the description adds genuinely useful behavior: dry_run defaults to true, real writes require confirmation unless SPOTIFY_MCP_CONFIRM=never, and the underlying endpoint. It does not contradict the non-destructive hint, though it omits mention of auth scopes or rate limits.

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?

Three tight sentences, front-loaded with the action and endpoint, followed by the rationale and safety gating. No wasted words.

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?

An output schema exists, so return values need no explanation. Endpoint, safety mode, confirmation policy, and API-version context are all covered, leaving nothing an agent needs 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 coverage is 100% and every parameter (including the public caveat and dry_run meaning) is already documented in the schema. The description reinforces dry_run's default but adds no syntax or format detail beyond the structured fields, so the baseline 3 applies.

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?

States a specific verb and resource ('Follow a playlist') plus the precise mechanism (PUT /me/library). It clearly distinguishes itself from siblings like unfollow_playlist and check_playlist_following.

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?

Explains why this tool is now the only path to follow a playlist (endpoints removed Feb 2026) and notes dry_run defaults to true while writes need confirmation. No explicit when-not-to-use or sibling alternative is named, though the alternatives are largely gone by construction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds real value beyond that by disclosing the scope of the response payload (item and progress only), letting the agent anticipate a lighter result set than the sibling. It does not mention auth or rate limits, but neither is critical for a poll.

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 tightly packed sentences with zero filler; the payload scope is front-loaded immediately followed by the routing instruction. Every clause earns its place.

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?

For a simple read-only poll with no output schema, the description covers what is needed: purpose, payload scope, and the sibling alternative. Nothing an agent requires in order to choose and call this tool 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% – market, response_format, and additional_types are each fully documented in the schema, including defaults and enum meanings. The description adds no parameter guidance, so the baseline of 3 applies.

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?

States a specific action (poll what is playing right now) and scopes it precisely with 'lightweight' and 'the item and progress only', which distinguishes it from the richer get_now_playing sibling named in the same sentence.

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?

Explicitly names the alternative tool (get_now_playing) and states the condition that selects it ('For full session state ... use get_now_playing instead'). This is textbook when-to-use/when-not-to-use routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description is not required to cover safety. It adds useful behavioral context by disclosing that the same rows are available as a resource without a tool call, and that the raw API object is accessible.

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 short sentences with zero waste. Purpose is front-loaded, and the resource alternative is appended as useful supplementary context.

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 is simple and read-only, with a fully documented schema and annotations. The description adds the resource alternative, which is valuable; the lack of output schema means return shape need not be explained in detail.

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 coverage is 100% and the schema fully documents both parameters (max_results and response_format), including defaults and enum values. The description adds no additional parameter-level detail, so the baseline of 3 applies.

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?

States a specific verb ('List') and resource ('Spotify Connect devices') with no ambiguity. No sibling tool covers device listing, so an agent can distinguish it immediately.

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?

Provides a concrete alternative access path via the spotify://player/devices resource and notes that '?format=json' returns the raw API object. It does not explicitly state when to call the tool versus reading the resource, but the context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true and idempotentHint=true, covering the safety profile. The description adds pagination behavior, but this largely restates the fetch_all schema description ('Walk every page') rather than offering new behavioral context like rate limits or result-size caps.

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 with no filler; the primary purpose is front-loaded and the pagination note is a single compact clause. Every word earns its place.

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?

For a read-only list tool with strong parameter documentation, the description covers the main pagination modes. However, it does not explain how fetch_all interacts with max_results, nor describe the return shape — and there is no output schema to compensate.

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%, so every parameter already has documented meaning. The description mentions fetch_all, limit, and after, but adds no new semantic detail beyond the schema's own descriptions.

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?

Description states the verb and resource explicitly: 'Get the artists the user follows.' The scope is clear and matches the tool name. It does not explicitly contrast with sibling tools like export_followed_artists or check_following_artists, so it lacks explicit sibling differentiation.

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?

Provides clear pagination guidance ('fetch_all=true walks every page; limit/after page manually'), which tells the agent when to use the fetch_all mode vs manual paging. However, it does not address when to prefer this tool over related siblings such as export_followed_artists or check_following_artists.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds real value beyond that by disclosing the breadth of state returned (shuffle/repeat mode, active device, volume) rather than just item+progress, though it says nothing about auth requirements or rate limits.

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, zero filler. The scope statement is front-loaded and the sibling routing note is compact and immediately actionable.

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?

Despite having no output schema, the description enumerates what is returned, covering the gap. With read-only annotations and fully documented optional params, an agent has everything needed to call this correctly.

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 all three parameters (market, response_format, additional_types) carry their own descriptions, defaults, and enum semantics. The description adds no parameter-level detail, so the baseline 3 is appropriate.

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?

Names a specific verb+resource (full device/session state for what is playing now) and enumerates the returned facets: item, progress, shuffle/repeat, active device, volume. It explicitly contrasts itself with the sibling get_currently_playing, so an agent can choose without opening either schema.

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?

States the alternative by name and the condition that selects it: 'For a lightweight item+progress poll use get_currently_playing instead.' This is an explicit when-to-use-this-vs-that routing rule.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds real behavioral context beyond that: market relinks tracks to a country and flags unavailable ones, and fields/additional_types trim the payload across both the metadata read and the item pages.

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, purpose front-loaded, then parameter behavior. Dense but every clause carries information. The second sentence crams several parameters together, but no sentence is wasted.

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?

For a 10-parameter tool with no output schema, the description covers identity, market and field-trimming but omits response_format (concise/detailed/json — a major output-shape decision), pagination (limit/offset/fetch_all/max_results), and the id/playlist_id alias. It is adequate but leaves notable gaps for an agent to fill from the schema alone.

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 coverage is 100%, so baseline is 3, but the description adds value beyond the schema by clarifying that fields/additional_types are forwarded to both the metadata read and the item pages, and that market affects linkage/unavailability rather than simple filtering. It says nothing about response_format, limit/offset, or fetch_all semantics.

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?

States a specific verb and resource: retrieves a playlist's metadata (including cover image) and items. This implicitly separates it from siblings like get_playlist_items and get_playlist_cover, which return only one half, though no sibling is named explicitly.

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?

The description explains what market, fields and additional_types do and notes they are forwarded to both the metadata read and item pages, which implies when to reach for them. It never states when to prefer this tool over get_playlist_items, get_playlist_cover, or search_within_playlist, so usage remains inferred rather than guided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds genuine context with the pagination and quota note ('GET /playlists/{id}/items paged'), but does not say how paging interacts with max_results or what the result shape looks like.

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 compact sentences with no filler, and the core purpose is front-loaded before the quota note. The 'Quota:' fragment is terse to the point of being slightly cryptic.

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?

For a read-only listing tool with no output schema and fully documented parameters, the description covers what is returned and how it is fetched. It does not explain result ordering defaults or paging limits, but nothing critical to a correct call 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%, with sort, max_results, playlist_id and response_format all documented including defaults and enums, so the schema carries the load. The description adds no parameter syntax or format detail beyond the output fields it mentions.

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?

States a specific verb and resource ('List when each track was added to a playlist') plus the fields returned (added_at, added_by), so the agent knows this is an added-date listing rather than a plain item listing. It stops short of explicitly naming the close sibling get_playlist_items, so it is clear but not sibling-differentiated.

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?

There is no when-to-use, when-not-to-use, or alternative guidance, despite several near-neighbors (get_playlist_items, get_playlist, search_within_playlist). Usage is only inferable from the phrase 'when each track was added'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true and idempotentHint=true, covering the safety profile, and the description is fully consistent with them (no contradiction). The description adds only the small detail that 'URLs' is plural, hinting that multiple image sizes may be returned. It does not disclose return shape, auth requirements, or rate limits, but with annotations carrying the safety burden, a 3 is appropriate.

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?

A single focused sentence with zero filler, front-loaded with the verb and resource. It is efficiently sized for a simple getter, though the brevity could have been leveraged to add sibling differentiation or usage context without becoming verbose.

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?

For a simple read-only getter with 100% schema coverage and safety annotations, the description is largely adequate. Gaps remain: no description of the return format despite the response_format parameter, and no routing between cover-related siblings (upload/clone/compare). The schema's note that 'id' matches get_playlist partially compensates by linking to a sibling's id format.

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%, so all four parameters (id, playlist_id, max_results, response_format) are already documented in the schema. The description adds nothing about parameters, so the baseline 3 applies. Notably, the schema's max_results and response_format parameters suggest the tool may behave more richly than the one-line description implies, but the schema itself documents them adequately.

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 ('Get') and resource ('a playlist's cover image'), and specifies the output ('URLs'). This distinguishes it from siblings like upload_playlist_cover, clone_playlist_cover, and compare_playlist_covers via the action verb. However, it doesn't explicitly name those alternatives, so differentiation is implied rather than stated.

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?

No guidance is provided on when to use this tool versus alternatives. The description never mentions the cover-related siblings (upload/clone/compare) or any condition that would select this tool over them. An agent must infer usage entirely from the tool name and the verb in the description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already mark this as read-only and idempotent, so the safety profile is covered. The description adds real behavioral context about single-page listing and market-based relinking/flagging, but it does not disclose pagination behavior beyond the single-page claim and says nothing about the return shape or how fetch_all interacts with the stated single-page behavior.

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 tight sentences front-load the core behavior and then immediately point to the most decision-relevant parameters. Every clause earns its place, with no filler or redundant restatement of the schema.

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 schema is exhaustive and annotations cover safety, so the description does not need to repeat everything. Still, with no output schema and a 10-parameter tool, the description leaves the fetch_all behavior and return format unmentioned, and 'single page' could mislead an agent into ignoring the built-in multi-page fetch option.

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 coverage is 100%, so the baseline is 3; the schema already thoroughly documents market, fields, additional_types, fetch_all, and the rest. The description essentially restates what market, fields, and additional_types do without adding new meaning, so it neither hurts nor materially improves parameter understanding.

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 clearly states the verb ('List') and resource ('a playlist's items'), and adds the scope 'on a single page' which helps set boundaries. It is not as strong as it could be because it never names a sibling like get_playlist to explicitly differentiate, but the purpose is unambiguous.

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?

The description gives useful parameter-level guidance ('Use market to relink tracks and flag unavailable ones, and fields/additional_types to trim the payload'), implying when options matter. However, it never states when to choose this over nearby alternatives like get_playlist, get_playlist_followers, or playlist_snapshot, and it omits mention of fetch_all despite saying 'a single page'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare read-only and idempotent behavior. The description adds useful context beyond annotations: the quota cost (2 GETs) and the concurrency reason for requesting snapshot_id, though it does not detail return shape or pagination.

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 short sentences/fragments with zero filler. It front-loads the returned values and then the quota constraint, so every element earns its place.

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?

For a simple read-only snapshot tool with supporting annotations and a fully described schema, the description states the core return values and quota cost. It could say more about how max_results interacts with the count or what response_format controls, but it is largely complete.

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%, so playlist_id, max_results, and response_format are already documented in the schema. The description adds no parameter-specific syntax, defaults, or selection guidance, so the baseline of 3 applies.

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?

States the specific data it exposes (snapshot_id and item count) and a purpose (optimistic concurrency), which distinguishes it from playlist-item tools. However, it never says 'playlist' and does not explicitly contrast itself with siblings like get_playlist or get_playlist_items.

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?

Mentions optimistic concurrency as a use context and quota cost, implying when it is useful. It does not give explicit when-not guidance or name alternative tools for cases where full playlist data or items are needed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnly and idempotent, but the description adds real non-structured context: the read-cost quota breakdown (1 read, plus one GET /me/player for enriched/runtime, plus one catalog read for the context label). It omits return-shape details, but the quota disclosure is genuinely useful cost information.

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?

Three compact sentences, front-loaded with the core action, then scope, then alternative, then cost. No filler; every clause carries actionable information.

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?

With no output schema, the description adequately conveys what comes back (contents, runtime, repeats) and the cost profile. Minor gap: it doesn't hint at pagination or max_results behavior for large queues, though the schema covers the cap.

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 coverage is 100%, so 3 is the baseline, but the description goes beyond the schema by tying specific parameter values (view=enriched, include=runtime, context label) to their request-cost implications, which the schema does not express.

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?

Opens with a specific verb+resource ('Read the playback queue') and immediately scopes it to queue contents (now playing, up next, runtime, repeat). It explicitly routes lookahead intent to a different tool, separating it from siblings like get_now_playing and skip_next.

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?

States the use case ('queue CONTENTS') and names the alternative ('Use peek_next for a short lookahead'), giving the condition that selects each. An agent can choose correctly without opening a schema.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true and idempotentHint=true, covering the safety profile. The description adds behavioral detail about fetch_all ignoring limit/offset and output being capped by max_results, which is useful beyond annotations. It doesn't describe return format but that's not required here.

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 with zero fluff. The core purpose is front-loaded, and the important behavioral notes about fetch_all and max_results are concise and immediately actionable.

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?

For a read-only list retrieval with 6 well-documented parameters, the description covers the key decision points (fetch_all, max_results cap). It doesn't specify return format, but given no output schema and annotations covering safety, the description is sufficient for correct invocation.

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%, so each parameter already has a clear description. The tool description adds no new parameter meaning beyond what the schema provides; it merely references fetch_all and max_results without additional detail. Baseline 3 is appropriate when the schema carries the burden.

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: 'Get albums saved in the user's library.' It clearly distinguishes from sibling tools like get_saved_tracks and get_saved_shows by focusing on albums. The name and description together make the purpose unambiguous.

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?

The description provides clear context on when to use pagination behavior: 'Set fetch_all=true to retrieve the entire collection.' It also explains the max_results cap. It does not explicitly contrast with alternatives, but the name and context make the appropriate use case obvious.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations only cover read-only/idempotent safety, yet the description discloses a wealth of behavior beyond them: a fixed quota of 6 GETs, one attempt per collection with rate limits surfaced rather than retried, unreadable collections reported with a reason and excluded from totals (never reported as 0), and playlists counted separately from the library total. This is exactly the operational context an agent needs.

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?

Front-loaded with the snapshot purpose, then layers in the edge cases. It is dense with clauses, but nearly every sentence carries decision-relevant information (total scope, unreadable handling, quota), so little is wasted.

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?

For a one-optional-parameter read tool with no output schema, the description fully explains what is returned (per-collection counts plus a total), how playlists relate to the total, and how failures appear. Nothing an agent needs to call or interpret it 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 coverage is 100% and the single response_format enum is fully described in the schema, so the baseline is 3. The description adds no meaning about response_format, and its limit/quota notes are internal mechanics rather than parameter guidance.

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?

States a specific verb+resource ('Library size snapshot: counts for tracks/albums/shows/episodes/audiobooks/playlists') that clearly separates it from the many sibling list/search tools (get_saved_tracks, search_saved_albums, etc.). The agent can tell this returns counts, not items, without opening the schema.

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?

The 'no item paging' and 'limit=1 reads' phrasing implies this is the cheap-counts alternative to the listing tools, but it never explicitly names a sibling or states when to prefer this over get_saved_tracks/get_saved_albums. Usage is strongly implied rather than routed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true and idempotentHint=true, and the description adds behavioral context by explaining the fetch_all behavior and output capping via max_results with its default from SPOTIFY_MCP_MAX_ITEMS. This adds value beyond the annotations by clarifying pagination and limits, though it doesn't cover auth or rate limits.

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?

Three sentences, each earning its place: purpose, fetch_all hint, and output cap. No redundant phrases or filler. The most important info is front-loaded in the first sentence.

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?

For a read-only list tool with six params and no output schema, the description covers the non-obvious behavior (fetch_all, max_results cap) while the schema fully documents the rest. It doesn't explain response_format or market, but those are in the schema, so the description is adequate for correct invocation.

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% with each parameter fully documented. The description reiterates fetch_all and max_results semantics that already exist in the schema (e.g., schema says 'Fetch all pages instead of one page (ignores limit/offset)' and max_results default), adding no new meaning. Baseline 3 is appropriate.

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 clearly states 'Get podcast episodes saved in the user's library' with a specific verb and resource. It distinguishes from siblings like get_saved_tracks, get_saved_albums, and get_saved_shows by specifying 'podcast episodes' and from search_saved_episodes by indicating retrieval of the entire saved library.

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?

The description offers usage guidance for the fetch_all and max_results parameters, but does not say when to choose this tool over alternatives like search_saved_episodes or get_episode. There is no explicit when-to-use or when-not-to-use context relative to siblings, so it relies on implied usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds useful behavioral context by mentioning that output is capped by max_results and that fetch_all retrieves the entire collection, which goes beyond the annotations without contradicting them.

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 with no extraneous information. The purpose is stated first, followed by the most relevant options (fetch_all and max_results). Every word earns its place.

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?

For a read-only list tool with 5 parameters fully documented in the schema and safety covered by annotations, the description is sufficient. It explains the core behavior and key options, though it does not describe return format or pagination details, which are partially covered by the schema.

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 coverage is 100%, so all parameters are documented. The description reiterates fetch_all and max_results behavior but adds little beyond what the schema descriptions already provide. The baseline of 3 is appropriate given the schema carries the parameter documentation.

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 clearly states the tool retrieves podcast shows saved in the user's library, specifying a distinct resource ('saved shows') that separates it from siblings like get_show_details or list_show_episodes. The verb 'Get' and the resource are explicit and unambiguous.

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?

The description implies usage for fetching saved shows but does not explicitly differentiate from list_saved_shows or other show-related tools. It offers internal guidance on fetch_all and max_results but no when-to-use vs alternatives, relying on the name to convey context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds meaningful behavioral details not in annotations: fetch_all toggles full-collection retrieval, and max_results caps output with an environment-driven default. This is exactly the kind of context that helps an agent predict cost and scope.

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?

Three tight sentences: the purpose comes first, followed by the two behavioral knobs that matter. No filler, no repetition of schema content. Efficient and front-loaded.

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?

For a read-only collection fetch with no output schema, the description covers the main behavioral questions: what it returns, how to get everything, and how results are capped. The remaining params (limit, offset, market, response_format) are fully documented in the schema, and response_format's enum explains the return shape. Complete enough given the tool's simplicity.

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 descriptions cover 100% of the 6 parameters with types, defaults, ranges, and enums, so the description doesn't need to re-document them. The description does reinforce the two decision-relevant params (fetch_all, max_results) in plain language, adding a small amount beyond schema. Baseline 3 is appropriate.

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?

States a specific verb, resource, and collection semantics: retrieves tracks saved in the user's Liked Songs. This distinguishes it from siblings like get_saved_albums, get_saved_episodes, and search_saved_tracks. Also surfaces the key options fetch_all and max_results, making the tool's scope immediately clear.

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?

Gives clear operational context: how to request the full collection (fetch_all=true) and how output is bounded (max_results, defaulting to SPOTIFY_MCP_MAX_ITEMS). It does not explicitly name alternatives or exclusions, but the read-only, single-collection scope is unambiguous. No misleading guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.