sounds

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

No annotations exist, so the description carries the full burden. It discloses important behavioral traits: rate limiting per client, specific error handling ('relay the note verbatim'), output licensing (CC0), and latency (10-60s). It could go further by explaining whether the operation is asynchronous or what success returns, but it covers the most critical behavior well.

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 tight and front-loaded: purpose first, then usage guidance, then rate limit and error handling, then legal/latency. Every sentence carries distinct, needed information with 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 two-parameter tool with full schema coverage, the description covers purpose, alternatives, rate limiting, error behavior, licensing, and latency. However, there is no output schema and the description never states what a successful call returns (e.g., audio URL, job ID, or binary data), which is a notable gap for an agent that must invoke and interpret 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 description coverage is 100%, so the baseline is 3. The description's mentions of 'English text description' and '1-12 seconds' repeat what the schema already documents, adding no new parameter-level meaning. It does not introduce constraints, examples, or clarifications beyond schema 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?

The description opens with a precise verb and resource: 'Generate a new sound effect from an English text description,' which clearly distinguishes it from the sibling get/search tools. It reinforces this by explicitly naming the sibling tools to try first, leaving no ambiguity about what this tool does uniquely.

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 guidance by stating this is a 'last resort' and telling the agent to try get_role_sound / get_sound_set / search_sounds first because the library covers most events. It also adds a practical constraint (3/day rate limit) and how to handle rate-limit errors, which further informs usage decisions.

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 no annotations provided, the description carries the full responsibility for behavioral disclosure. It indicates a read-only operation by the word 'check', but does not mention return values, possible statuses, error behavior, or whether the job is removed after completion. This is thin for a tool that is likely used asynchronously.

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, direct sentence with no filler or repetition. It front-loads the action and object, and is appropriately sized for a tool with one required parameter.

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?

There is no output schema, annotations, or richer context, so the description is the sole source of information. It does not explain what kind of status information is returned, how to interpret completion states, or how long a job might take. For an async job-status tool, this leaves 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 description coverage is 0%, so the description must compensate for the bare parameter schema. It only parrots the parameter name 'job_id' without explaining the format, source, or lifecycle of the ID. The term 'generation job' adds some context, but not enough to fully understand the parameter 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?

The description states a specific action ('Check the status') on a specific resource ('a generation job'), and identifies the key identifier ('by job_id'). This clearly distinguishes it from the sound-focused sibling tools, which are about generating or retrieving sound assets rather than job status.

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 should be used when an agent needs to check the status of a previously created generation job. However, it does not explicitly state when to use it versus alternatives, nor does it mention that job_id likely comes from a generate_sound call.

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. It discloses role alias normalization, return contents (URLs, alternates, family page), style effects, loopable WAV handling, and the not_found response for unknown roles.

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 dense but efficient, front-loading the primary use case and alternating with concrete examples. It is longer than average, yet nearly every sentence adds useful operational detail.

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 thoroughly covers return format, alternatives, error behavior, loop handling, and role discovery via an endpoint. It also routes to sibling tools where appropriate, leaving little ambiguity for an agent deciding whether and how to invoke 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?

The schema already documents both parameters with 100% coverage, but the description adds real value: it enumerates accepted aliases, explains what 'balanced' means as the default, and clarifies the acoustic character of each style option.

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: it returns the default sound for a given role/event, and provides concrete examples of roles it accepts. It also distinguishes itself from siblings by naming get_sound_set and search_sounds as alternatives for different 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 explicitly says to use this tool FIRST for event/interaction sound requests, names get_sound_set for whole kits, and directs free-text descriptions to search_sounds. This gives clear when-to-use and 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?

No annotations are present, so the description carries the full burden of conveying behavior. It communicates a read-only operation and describes the return payload, but does not mention error behavior, permissions, or side effects. This is adequate for a simple get-by-slug tool but not deeply transparent.

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 efficient sentence that front-loads the verb and resource, then lists the valuable return fields. There is no filler or 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?

With one simple parameter and no output schema, the description lists the key return categories (download URLs, generation prompt, acoustics, character labels), which is enough for an agent to decide on invocation. It does not exhaustively specify response structure, but that is not critical for calling the 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?

The input schema has 100% coverage for the single 'slug' parameter, including an example, so the description adds no necessary parameter information. Baseline 3 applies because the schema already handles parameter semantics fully.

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 ('Get') with a clear resource ('full metadata for one sound') and a specific identifier ('by slug'). It also enumerates distinctive contents (download URLs, generation prompt, measured acoustics), which makes it easily distinguishable from list/search/generate 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?

The description clearly implies when to use the tool: when you have a sound slug and need full metadata. It gives no explicit exclusions or alternative tool names, but the context is clear enough that an agent can infer the appropriate use case.

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 no annotations provided, the description carries the behavioral burden and does meaningful work: it explains the selection logic ('picked by measured acoustics') and exactly what is returned: slugs, MP3/WAV URLs, acoustics, loopability, alternates, and a role-to-URL map. It does not mention potential async behavior, rate limits, or auth expectations, but those are not obvious requirements for this tool based on the description.

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: purpose, usage guidance, return contract, then style and scenario sets. It front-loads the most important information, though it partly duplicates the schema's enum list, which keeps it from being maximally 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?

Even with no output schema, the description tells the agent what will be returned and how the set parameter changes the result. The optional parameter and default are covered by the schema, and the description provides enough context about roles, styles, scenarios, and alternatives for an agent to invoke 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?

The schema already documents the 'set' enum, but the description adds substantial meaning by explaining what each style sounds like (ui-crisp: dry, tight, bright; ui-spacious: room reverb, longer tails) and what scenario sets are for, including the specific ai-coding-tool cues. This is well beyond what the enum labels provide.

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 action and object: 'Get a coherent set of sounds for an app or game in one call.' It clarifies the scope with one sound per role and explicitly distinguishes this tool from get_role_sound, so an agent can tell which tool to use without needing the sibling list.

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 explicitly states when to use this tool ('when the user wants a whole kit rather than one event') and names the alternative ('for a single event use get_role_sound'). It also gives a clear decision between style-based and scenario-based sets, covering the main usage choice.

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 no annotations provided, the description fully carries behavioral disclosure. It details exact-match-first-then-semantic ordering, the 'never empty' guarantee, hotlinkable URLs with no API key or attribution, and the full result structure including acoustics, character labels, loopability, and match/score semantics with value ranges.

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 every sentence adds distinct value: purpose, usage routing, result ordering, and return field details. It is slightly dense, but the structure is logical and front-loaded with the core purpose before the caveats and details.

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?

There is no output schema, so the description must document return values; it does so thoroughly, covering URL format, acoustics, character labels, loopability, and the exact match score meanings and range. It also explains result ordering and the non-empty guarantee, leaving no critical gap for an agent to call and interpret 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%, with all three parameters already documented (limit default/max, query examples, category slug list). The description adds behavioral context such as result ordering and match semantics, but it does not add new meaning to the parameters themselves beyond what the schema already provides. A 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 opens with a specific verb and resource: 'Free-text search over 4,600+ free CC0 sound effects.' It also explicitly distinguishes itself from get_role_sound by naming the exact condition when the sibling should be used instead, so an agent can tell tools apart without inspecting schemas.

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 an explicit when-to-use rule: use for descriptions that do not name a UI/game event, and call get_role_sound first for named events. This directly routes an agent to the correct sibling and provides concrete examples of each case.

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