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

No annotations are provided, so the description carries the full burden. It hints at a read-only scoring operation by promising 'missing dimensions and suggestions', but says nothing about whether this reads or mutates session state, what permissions or session context it needs, or whether the seed library dependency must be set up first.

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 dense sentence that front-loads the operation and appends the return values. Nothing is redundant, though domain jargon ('Music DNA dimensions', 'seed library') is used without definition.

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 tool with no annotations, no output schema, an undocumented parameter, and undefined domain terms, the description leaves too much unspecified. It never explains what 'Music DNA' or the 'seed library' refer to, so an agent cannot reliably decide when this analysis is appropriate.

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 0%, with only type and length constraints on intent_text. The description implies the parameter is a free-text statement of user intent but gives no guidance on expected content, format, or length, leaving an undocumented 4000-char string field to the agent's guesswork.

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 ('Score clarity of user intent') against a specific domain resource ('Music DNA dimensions and seed library') and describes what it returns. It does not distinguish itself from siblings like map_music_dna or match_top_patterns, which also operate on Music DNA concepts.

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 prerequisites, and no mention of alternative sibling tools. An agent cannot tell from this description whether to call analyze_intent before, after, or instead of map_music_dna or suggest_keywords.

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?

No annotations are provided, so the description carries the full behavioral burden, and it discloses very little. The 'Quality target: seed library Neon Horizons / Liminal Tides' line gives a useful calibration reference for output quality, but there is no statement on side effects, determinism, permissions, or how max_chars affects the result.

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 written sentences with the core action front-loaded and no filler. The quality-target clause is somewhat opaque to a reader without the referenced seed library, but it earns its place as a calibration hint.

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 tool with a deeply nested DNA schema, optional overrides, and three formatting toggles, and with no output schema or annotations, the description is far too thin. An agent cannot tell how DNA fields map to the produced Style field, how truncation via max_chars works, or what the returned artifact looks like.

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 40% and the description adds no per-parameter detail. 'Music DNA' and 'journey overrides' loosely map to the dna and journey params, but max_chars, include_bpm_key, and include_exclude are neither documented in the schema nor explained here, leaving the toggles' effect on output unclear.

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 artifact: 'Compose a full Suno Custom Style field from Music DNA.' The input source ('Music DNA') implicitly links it to the map_music_dna sibling, so the agent can distinguish producer from consumer. It stops short of explicitly contrasting with siblings like suggest_keywords, but the resource 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 phrase 'from Music DNA (+ optional journey overrides)' implies the upstream dependency and the optional-input condition, but there is no explicit when-to-use, when-not-to-use, or named alternative. Usage must be inferred from the data-flow phrasing rather than 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?

No annotations are provided, so the description carries the full burden. It usefully discloses that image_url is treated purely as a text hint with 'no media download', but omits permissions, determinism, latency, and any failure behavior. Listing returned fields is helpful but doesn't substitute for 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?

Two dense, front-loaded sentences with no filler; the operation and its output fields lead. The parenthetical about no media download is worth its space.

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, listing the returned attributes (emotion, genre, textures, energy arc, etc.) is genuinely necessary and present. However, with 5 parameters, 40% coverage, and zero annotations, the definition leaves parameter behavior and operational caveats under-specified.

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 only 40% (text and image_url documented; bpm_hint, genre_hint, instrumental undocumented). The description clarifies the image_url semantics and reiterates 'free text', which partially compensates, but does not explain the three hint/flag parameters.

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 ('Extract') and a concrete resource ('structured Music DNA from free text'), so the agent knows the transformation. It does not distinguish itself from siblings like analyze_intent or suggest_keywords, which occupy overlapping semantic space.

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 or when-not-to-use guidance, and no routing to alternatives among the six sibling tools. The 'image_url as text hint only' note is a behavior detail rather than selection 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?

No annotations exist, so the description carries the full behavioral burden. It does disclose that results are restricted to 'high-rated' items, which is genuine behavioral context, but says nothing about ranking, result count behavior, or latency/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?

A single front-loaded sentence with no filler, but the extreme brevity is under-specification rather than true efficiency for a tool with an undocumented 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?

With no annotations, no output schema, and 0% parameter coverage, the description leaves key gaps: how many results come back, how matches are ranked, and what 'pattern cards' versus 'library entries' means in the result set.

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 0%, so the description must compensate. It covers only the 'query' parameter implicitly ('free-text query') and gives no hint about the 'limit' parameter's default of 3 or maximum of 10.

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 similar') and resource ('high-rated pattern cards and library entries') with the input mode ('free-text query'). An agent knows what the tool returns, but the description never contrasts it with plausible siblings like suggest_keywords or analyze_intent.

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, when-not-to-use, or alternative guidance is given. The phrase 'for a free-text query' weakly implies the input condition, but nothing tells an agent how to choose between this and the other five pattern/music tools.

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?

No annotations exist, so the description carries the full burden, and it does disclose real behavioral facts: no network calls, no credit spend, no audio evaluation — i.e. a pure local validation step. It stops short of stating what validation runs, whether anything is persisted, or how invalid input is reported, which matters for a 10-required-param 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?

A single front-loaded sentence that separates what the tool does from what it does not, with no filler. Every clause carries 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?

For a tool with 11 parameters, 10 of them required, no annotations, no output schema, and zero schema descriptions, this one-liner is far too thin. The agent knows the tool's scope but nothing about the inputs it must supply or what it receives back.

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 0% across 11 parameters, and the description compensates for none of it. Constraints like the owner/engine enums, the 1-8 candidate range, the USD budget semantics, and the role of 'artist_profile_ref' versus 'work_id' are entirely undocumented.

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 concrete verb ('prepare') and a named artifact ('validated provider-neutral music packet'), and it defines the boundary of the operation by listing what it does not do. 'Music packet' is internal jargon, but no sibling (map_music_dna, build_style_field, suggest_keywords, analyze_intent, match_top_patterns) plausibly covers the same ground, so an agent can still route here correctly.

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 exclusions ('no API calls, credit authorization or audio verdict') implicitly tell the agent this is the pre-execution, zero-cost preparation step, which is useful routing context. However, it names no alternative tool, states no preconditions, and never says what to do with the packet afterwards.

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?

No annotations are provided, so the description carries the full behavioral burden. 'Suggest' implies a read-only generative operation, but nothing states whether output is deterministic, how many keywords come back beyond the 'limit' param, whether mood/genre meaningfully change results, or any latency/cost characteristics.

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 tight sentence with no filler, front-loading the verb and the produced artifact. It is efficient, though brevity is achieved partly by omission rather than by precision.

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?

A four-parameter tool with no annotations, no output schema, and 0% schema description coverage needs the description to explain inputs and return shape. Instead it gives one line, leaving the agent without enough to call it confidently or to know what the returned keywords look like.

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 0% and there are four parameters, so the description must compensate — it does not. It names vibe, genre and mood (restating schema property names) but adds no format, example, or constraint semantics, and it omits the 'limit' parameter entirely.

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 ('Suggest') and resource ('vibe/DNA keywords') plus the inputs that shape the suggestion, so an agent can tell what it produces. It does not, however, differentiate itself from similarly-themed siblings such as map_music_dna or build_style_field, which also operate on vibe/DNA concepts.

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 conditions, and no mention of any alternative. With five overlapping siblings in the keyword/DNA/style space, the agent gets no signal about which tool to pick for which intent.

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