Generate a video on Dare

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

Discloses the credit spend with a concrete cost estimate, the async nature of rendering, typical 5–15 minute latency, and immediate generation-id return behavior. This adds meaningful behavioral context beyond the annotations, which only mark the operation as non-read-only and non-idempotent.

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?

Four dense, front-loaded sentences cover the core action, cost, latency/async behavior, and reference workflow with no filler. Every sentence 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 complex, credit-spending async tool with no output schema, it covers return behavior, cost, latency, polling, and media references. The remaining parameter details are already supplied by the rich, fully described input schema.

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 covers all 11 parameters at 100%, so the baseline is 3. The description adds useful guidance on wait_seconds (prefer 0 and poll) and reference_storage_keys workflow, and clarifies the default model. This earns a 4 but not 5 because most per-parameter semantics remain in 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?

States the exact operation: 'Generate a video from a text prompt on Dare', with a concrete default model (Seedance 2.5). This clearly separates it from dare_generate_image and dare_get_generation.

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 instructs to call dare_estimate_cost first, poll with dare_get_generation instead of blocking, and upload references with dare_upload_media before invoking. It also tells when to set wait_seconds, giving clear workflow guidance relative to sibling tools.

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