FreqBlog Music Metadata

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

The description adds value beyond annotations: it reveals the tool returns data (not mutates), costs 5 quota units, and details the output structure. Annotations already declare readOnlyHint=true and openWorldHint=true; the description reinforces non-destructive behavior and adds cost and output specifics.

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 efficient at 4-5 sentences, starting with the main action and then detailing arc, output, usage, and cost. It is front-loaded with the core purpose. Slightly dense but 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?

The description is comprehensive: covers input limits (2-100 tracks), arc options, output structure (flow_score, transitions, omitted ids), and even a usage hint (feed into DJ software). Given the tool's complexity and the presence of an output schema, the description adds ample context and covers all key aspects.

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. The description repeats schema info for 'arc' options and 'track_ids' meaning, but adds minimal extra context: start_track_id constraint 'must be one of track_ids'. No significant new meaning beyond schema definitions.

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's action: 'Order a crate of 2-100 catalog tracks into a beat-matched DJ set that follows an energy arc.' It specifies the resources (catalog tracks) and the output (setlist with transitions, score, etc.). This distinguishes it from siblings like suggest_next_track or score_transition, which focus on individual aspects.

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: when you have a crate of tracks and want a harmonically and tempo-smooth DJ set. It does not explicitly exclude alternatives or mention when not to use it, but the context is clear and no sibling differentiation is provided. The mention of cost provides a constraint.

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?

Given annotations (readOnlyHint=true, openWorldHint=false), the description adds context about no catalog lookup and no quota cost, which aligns with the read-only nature. It does not contradict annotations and provides additional behavioral details.

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 concise sentences that front-load the purpose and immediately convey core functionality. Every sentence adds value without redundancy.

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 tool's simplicity and presence of an output schema, the description is complete. It explains what the tool returns, what it does not (no catalog lookup), and how to use it in context with other tools.

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 has 100% description coverage, but the description adds meaning by explaining the harmonic logic (same key, relative major/minor, adjacent +/-1, extended +7/-7). This goes beyond the schema's simple parameter description.

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 returns harmonically compatible keys for DJ mixing given a Camelot key, specifying the types of keys (same, relative, adjacent +/-1, and optionally +7/-7). It distinguishes from the sibling 'find_tracks_by_key' by emphasizing that this is pure music theory with no catalog lookup.

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 describes when to use (to get harmonic compatibility for DJ mixing) and when not to (no catalog lookup). Suggests pairing with 'find_tracks_by_key' for actual track retrieval, providing a clear alternative.

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 openWorldHint=true. Description adds ordering logic and that each track contains full audio features, providing transparency beyond annotations without contradiction.

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, front-loaded with the core action, no wasted words. Every sentence adds value.

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 tool's simplicity, good annotations, and an output schema, the description covers return values, ordering, and use cases completely. No 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% with good descriptions. Description adds the ordering logic (closeness then popularity), which is not in the schema. This extra meaning justifies above 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?

Description clearly states the tool finds tracks near a target BPM, specifies ordering by closeness then popularity, and lists concrete use cases. It also distinguishes from sibling by mentioning combination with find_tracks_by_key.

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?

Description provides explicit use cases (DJ set planning, workout playlists, tempo-matching) and mentions an alternative (combine with find_tracks_by_key for key constraints). It does not list when not to use, 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 declare readOnlyHint=true and openWorldHint=true. The description adds details: accepted key formats (Camelot, Open Key, key name), ordering by popularity, and that results include full audio features. No contradictions.

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 well-structured sentences: first states purpose, second details parameters and alternatives. No wasted words, front-loaded with key 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?

Given output schema exists, return values need not be detailed. The description covers purpose, usage, key formats, ordering, and mentions full audio features. Directs to sibling tool for further needs. Complete for a simple 2-parameter 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 coverage is 100%, so parameters are documented. The description adds value by explaining the key formats more richly and mentioning that results are ordered by popularity, providing context beyond 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 'Find catalog tracks in a given musical key — for harmonic mixing and key-locked playlists,' clearly identifying the verb (find), resource (tracks), and purpose (harmonic mixing). It distinguishes from siblings like find_compatible_keys.

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 (find tracks by key) and when not to ('To discover which keys mix well with a given key first, use find_compatible_keys'), providing a direct alternative.

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 (readOnlyHint, openWorldHint), the description discloses behavioral traits such as null fields for fallback tracks, on-demand ingest behavior, queued response fallback (~15s), and terminal not-found for 7 days. 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 long but well-structured with bullet points and clear sections. Every sentence adds value, and the most important information (get features for one track, identifiers) is front-loaded. No redundancies.

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 complexity (5 params, 100% schema coverage, output schema exists), the description covers all necessary aspects: identifiers, fallback behavior, null fields, on-demand ingest, retry logic, and definitive not-found. It even mentions when to use a sibling tool (search_catalog). Very 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%, but the description adds significant meaning beyond the schema: explains the logic behind each identifier (e.g., spotify_id resolves <1% of catalog), validates constraints (artist required for short titles), and clarifies behavior like on-demand ingest. This far exceeds 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?

The description clearly states the tool gets audio features for one track, listing specific features (BPM, key, etc.). It distinguishes from siblings by noting it is the drop-in replacement for Spotify's deprecated endpoint and explicitly contrasts with search_catalog and get_audio_features_batch.

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 explicit guidance on which identifier to use (track, isrc, mbid, spotify_id) with trade-offs. It advises to call search_catalog for fuzzy names, and clarifies when spotify_id is not recommended. This effectively tells the agent when to use this tool vs 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?

Beyond annotations (readOnlyHint, openWorldHint), the description discloses critical behavioral traits: how bad entries are handled, billing conditions, return structure, and special statuses like invalid_no_query and over_limit. 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?

Well-structured with front-loaded main purpose, followed by clear details in separate paragraphs. Every sentence adds value, though slightly verbose in explaining ISRC behavior, making it not perfectly concise.

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 an output schema (not shown), the description thoroughly describes return values: counts, per-track result array, feature object same as get_audio_features, skipped items with reasons, and billing info. Completely covers what an agent needs to understand the tool's behavior.

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%, but description adds significant meaning: explains the relationship between isrc and track (exact match first, fallback), optional artist for accuracy, and consequences of missing both. This enriches the schema beyond its 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?

The description clearly states it retrieves audio features for many tracks in one call, ideal for analyzing playlists, and explicitly distinguishes from sibling get_audio_features by recommending that tool for single tracks.

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 advises when to use (batch of up to 50 tracks) and when not (single track, use get_audio_features). Details such as ISRC exact matching, no batch failure on bad entries, and instructions for handling over-limit items provide clear 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?

Adds extensive behavioral context beyond annotations: blending up to 5 seeds, genre re-ranking, score vs order relationship, genre_relation field behavior (primary seed, multi-seed nuance), no-id resolution, and quota cost. No contradiction with readOnlyHint or openWorldHint.

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?

Well-structured, front-loaded with purpose, then progressively reveals details (output fields, edge cases, modes, fallback). Every sentence adds necessary information; no fluff. Length is justified by complexity.

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?

Covers all aspects: seed specification, genre handling, output format, edge cases, cost. References sibling tool for comparison. Completeness is high given tool complexity and rich parameters.

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?

Every parameter gains extra context from the description: seed_tracks gets format example, track/artist fallback and echo, cross_genre modes explained, limit bounds. Despite 100% schema coverage, the description significantly enriches 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?

Explicitly states it provides recommended tracks for one or more seed tracks, acting as a drop-in for Spotify's removed endpoint. Clearly distinguishes from sibling 'suggest_next_track' by noting identical behavior for single seeds and explaining multi-seed differences.

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 detailed when-to-use guidance, including seed_tracks vs track+artist fallback, cross_genre modes, and how single vs multiple seeds affect genre_relation. References suggest_next_track for comparison, and explains parameter interactions (e.g., seed_tracks wins over track).

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 openWorldHint. The description adds substantial behavioral details: no exact graph exists, derivation via track vectors, scoring with same-genre lift and cross-genre penalty, and cost of 2 quota units. No contradictions.

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 well-structured with purpose first, then algorithm, return format, usage hints, and cost. It is somewhat lengthy but every sentence adds value. Slightly verbose for very concise standards, but still earns a high score.

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 algorithmic complexity and the presence of an output schema, the description fully covers purpose, return structure, invocation patterns (e.g., passing sample_track_id to other tools), and cost. No gaps identified for an agent to use the tool effectively.

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 already describes both parameters (artist and limit) adequately. The description does not add new meaning or constraints beyond the schema, so a 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?

The description clearly states the tool returns artists related to a seed artist, explicitly comparing it to Spotify's removed endpoint. It distinguishes itself from siblings by detailing its derived algorithm and naming specific use cases.

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 positions the tool as a drop-in replacement for Spotify's related-artists endpoint, giving clear when-to-use context. It lacks explicit exclusions or comparisons to other sibling tools like get_recommendations, but the context is strong enough for an agent to decide.

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?

Description details exact return structure (overall score, per-component scores, detail block with key/BPM/energy info, human reason) and explains mixing components (Camelot compatibility, BPM proximity, energy smoothness). Aligns with readOnlyHint 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?

Description is efficient with 4 sentences, front-loaded with purpose, and structured logically. Minor redundancy but overall concise.

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?

Covers all aspects: purpose, input sources, return fields, cost, and complements annotations (readOnlyHint, openWorldHint). No gaps given output schema existence.

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 covers both required parameters with descriptions. Description reinforces they are catalog itunes_track_ids and provides an example, adding value beyond 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?

Description clearly states it scores DJ transition compatibility between two tracks (0-100) and distinguishes from sibling tools like get_audio_features (individual track features) and suggest_next_track (track suggestion).

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?

Description provides context for when to use (pairwise scoring not available elsewhere) and where to obtain track IDs (search_catalog or get_audio_features). Lacks explicit when-not-to-use, but sibling list compensates.

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 openWorldHint=true, which are consistent. The description adds critical behavioral details: returns lightweight stubs (not audio features), ranking by relevance, and the seedable boolean with its implications for downstream tools.

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 well-structured, front-loading the core purpose, then providing usage guidance and warnings. Every sentence adds value without redundancy. It is appropriately sized for the complexity of the tool.

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 purpose, usage, edge cases (seedable: false), and workflow integration. The output schema exists to document return fields, so the description's focus on behavior and usage is appropriate and 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?

Both parameters (q and limit) are already described in the schema with 100% coverage. The description adds value by explaining that q accepts any mix of tokens and that limit caps results, but the schema already provides the basics. The extra context about seedable 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 it performs full-text search of the music catalog by track/artist/album tokens. It distinguishes itself from sibling tools by explicitly positioning this as the resolver for fuzzy names before calling get_audio_features.

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 explicit guidance on when to use (fuzzy/partial matches) and how to proceed (use the best match with seedable: true). Also warns against seeding with non-seedable hits and explains the alternative (get_audio_features first).

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 declare readOnlyHint=true and openWorldHint=true, which align with a read-only suggestion tool. Description adds value by stating cost (3 quota units), explaining genre-awareness defaults, and detailing output format. No contradictions.

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?

Reasonably concise given the information volume. Organized with clear purpose first, then output details, genre modes, and usage context. A few sentences could be tightened (e.g., 'It is the seed's sonic neighbours re-ranked for a clean mix'), but overall economical.

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 7 parameters, full schema coverage, and existing output schema, the description sufficiently explains output format (seed, count, suggestions array with details). Mentions pairing with build_setlist for workflows. Minor gap: no handling of invalid seed_track_id or error cases, but acceptable for a suggestion 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 covers 100% of parameters with descriptions. Description adds context for seed_track_id (acceptable sources) and cross_genre (behavior explanation), enhancing clarity beyond the schema's basic 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?

Clearly states verb (return, suggest), resource (catalog tracks to play NEXT), and scope (ranked by transition score). Distinguishes from siblings like score_transition by specifying it returns suggestions based on a seed, not a pair score. Mentions output includes score, components, reason, genre.

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?

Describes when to use (given a seed track), explains cross_genre modes, and suggests pairing with build_setlist. Lacks explicit when-not-to-use alternatives like score_transition or find_compatible_keys, but the purpose implies the distinction.

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 openWorldHint. Description adds significant behavioral context: cost model (1 quota unit, charged only on served result), nature of analysis (no audio upload, no extra compute), and detailed explanation of confidence/provenance fields. 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?

Description is comprehensive but somewhat long. However, it is well-structured with clear sentence breaks and front-loaded with the core purpose. Every sentence adds value, though slight trimming could improve conciseness.

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 tool's complexity and the presence of output schema, sibling tools, and 100% schema coverage, the description provides complete contextual coverage: explains return format, identifier usage, cost implications, and differentiation from sibling tools. No gaps remain.

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%, but description adds crucial semantics beyond simple parameter names: clarifies that exactly one identifier must be provided, explains the role of 'artist' as an accuracy enhancer, and provides context on when each identifier type is most effective (e.g., MBID/ISRC for AcousticBrainz coverage).

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 begins with 'Get a compact, HONESTLY-LABELLED tag list for a track', clearly stating the verb and resource. It enumerates specific tag types and distinguishes itself from get_audio_features and opaque taggers, providing strong differentiation from siblings.

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 states when to use alternatives: 'For the full numeric feature set use get_audio_features; for nearest tracks use a discovery tool.' Also provides detailed guidance on identifier selection, including when MBID/ISRC offer better coverage.

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