talking_gif

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

With no annotations provided, the description carries the full burden. It discloses a key behavioral trait: 'Free — spends no generations; it only re-orders mouth positions' — indicating this is a non-destructive, cost-free operation. It also clarifies the input dependency on pre-existing mouth data. However, it does not specify the return format (e.g., URL, base64) or whether the operation is synchronous, which are minor omissions given the tool likely returns a GIF URL.

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 sentences, front-loaded with the core purpose. The first sentence states exactly what the tool does; the second conveys cost and usage in one compact sentence. No redundancy or filler. It is highly concise and well-structured.

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 (6 parameters, nested object for visemes) and no output schema, the description covers the essential inputs and the key behavioral context (free, uses existing mouth positions). It explains the two input pathways and the dependency on prior vocal_animation output. It omits the return format, but the description's mention of 'animated GIF' as the output gives sufficient context for an agent to proceed. Overall, it is complete enough for effective use without excessive ambiguity.

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 modest value by explaining the mutual exclusivity of character_id and visemes and pointing to the source of visemes (get_vocal_animation_job). It does not elaborate on individual parameter semantics beyond what the schema already provides (e.g., mood, hold_ms, frame_ms), so it meets the baseline but does not exceed 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 action: 'Turn a line of text into an animated GIF of a character speaking it.' It clearly distinguishes the tool from siblings like vocal_animation (which generates mouth positions) and get_vocal_animation_job (which fetches visemes) by focusing on assembling a GIF from existing mouth data. The verb 'turn' and resource 'line of text' plus output 'animated GIF' 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 explicit when-to-use guidance: it's free and reuses mouth positions from vocal_animation, implying it should be used after obtaining those positions. It also gives concrete instructions on the two ways to supply input: 'Provide either character_id (with mouth positions stored on the character) or supply visemes directly as returned by get_vocal_animation_job.' This clarifies prerequisites and alternatives without requiring further research.

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