sounds

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

With no annotations provided, the description carries the behavioral disclosure burden and does so well by surfacing the 3/day rate limit, CC0 licensing, and 10-60s latency. It does not clarify whether the call is asynchronous or what the exact job/response semantics are, but it provides substantial operational context beyond the 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?

Three short sentences, each adding distinct value: the core purpose, the rate limit, and the output/licensing/latency constraints. There is no repetitive or filler content.

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 generation tool, the description covers the key constraints: duration range, rate limit, license, and expected wait time. The only notable gap is that it does not describe what the API returns (e.g., a URL, binary audio, or job reference), which matters more because no output schema is provided.

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 both parameters are already documented in the input schema. The description adds little new parameter meaning beyond restating 'English text description' and the 1-12 second duration range already present in the schema, so it stays at 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?

The description states a specific action ('Generate'), a clear object ('a new sound effect'), and the input modality ('English text description'), making its purpose unmistakable. The word 'new' plus the sibling retrieval tools (get_job, get_sound, search_sounds) makes the distinction between creation and retrieval obvious.

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 phrasing 'Generate a new sound effect' clearly implies this tool is for creating sounds rather than retrieving existing ones, and the sibling names reinforce that retrieval is handled elsewhere. It does not explicitly say 'use get_sound or search_sounds for existing sounds,' so it stops short of a fully explicit when/when-not statement.

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 burden of behavioral disclosure. 'Check the status' does signal a read-only operation, but the description does not mention possible status values, polling expectations, or behavior for an unknown or expired job_id.

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 short, focused sentence with no filler. It front-loads the action, resource, and parameter role, and every word contributes to understanding.

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-parameter read-only tool, the description is mostly adequate, but it does not explain what the status response looks like or how job_id relates to the generate_sound workflow. With no output schema, the description could usefully mention that job_id is returned by generate_sound and that get_sound is used once the job completes.

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 has 0% description coverage, so the description must compensate. The phrase 'by job_id' clarifies that the single required parameter identifies the generation job whose status is being checked, adding semantic context beyond the bare schema. It does not explain where job_id comes from, but the mapping is clear.

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, 'Check', and a specific resource, 'status of a generation job', and identifies the required input 'job_id'. This clearly distinguishes get_job from siblings like get_sound and search_sounds, which operate on sound resources 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?

No guidance is provided about when to use this tool versus alternatives. The description does not state that get_job should be used after submitting a generation job or before the sound is ready, leaving the agent to infer the workflow context from sibling names.

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, the description carries the full behavioral burden. It conveys a read-only retrieval operation through 'Get' and is transparent about what is returned, including download URLs and acoustics. It stops short of detailing error behavior (e.g., 404 for unknown slug) or side effects, but for a simple getter the verb plus return details provide substantial transparency.

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 leads with the primary action and then appends the key response contents. Every phrase earns its place; no filler or repetition.

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-parameter getter with no output schema, the description is complete: it states the lookup key, the resource, and the return contents. The sibling context (generate_sound, search_sounds, get_job) plus the schema example cover the remaining usage context.

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 'slug' with an example at 100% coverage, so the baseline is 3. The description adds only that the tool looks up 'by slug', which is consistent with the schema but does not add 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?

The description states a specific verb ('Get'), a clear resource ('full metadata for one sound'), and the lookup key ('by slug'). It also enumerates the metadata contents (download URLs, generation prompt, measured acoustics), which distinguishes it from siblings like search_sounds or generate_sound by making clear this is a single-item metadata retrieval.

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 slug and need full metadata for one sound, call this tool. However, it does not explicitly discuss when not to use it or how it compares to search_sounds (e.g., use search_sounds to find slugs) or get_job. The guidance is implicit rather than explicit.

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 burden of behavioral disclosure. It reveals that no API key is required, that returned URLs are direct and hotlinkable, and that each result includes acoustics and character labels. It does not mention rate limits or error behavior, but for a non-destructive keyword search the core behavioral traits are 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?

Two dense, well-structured sentences with no filler. The core action is front-loaded, followed by useful output and selection details. 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 search tool with no output schema, the description sufficiently explains the input style, licensing, URL output format, and result metadata. It relies on the schema for limit and category details and does not address sibling alternatives, but a caller can confidently invoke the tool with just this description.

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 query, limit, and category. The description complements the schema by explaining what the query does and what the results contain, but it does not add meaningful parameter-level detail beyond the structured descriptions, matching 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?

The description opens with a specific verb+resource ('Search ... sound effects by keyword') and clearly communicates a search/retrieval purpose. It is distinct from its siblings semantically ('search' vs 'generate'/'get'), though it does not explicitly call out the sibling tools, so it falls just short of full 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?

The description provides clear context for when to use the tool: when you need a CC0 sound effect by keyword and want direct, hotlinkable URLs without authentication or attribution. It does not explicitly name when-not-to-use alternatives, but it gives enough context to guide selection.

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