submit_video_generation

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

With no annotations present, the description carries the full behavioral burden and does a solid job: it discloses the async nature (returns task_id immediately), the exact endpoint being called, the billing model distinction, and the no-auto-retry policy. It doesn't mention rate limits, partial-failure semantics, or response shape, but for a latency-sensitive submission tool the key behaviors 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?

Three sentences with no filler, logically ordered: core purpose first, then billing/endpoint context, then the retry instruction. Efficient for a tool with 12 parameters. Slight opportunity would be to integrate the workflow link (submit→query) into that space, but nothing is wasted.

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 12 parameters, no output schema, and no annotations, the description covers the essentials: async contract, billing, endpoint, error-handling expectation. The schema handles param semantics thoroughly. The main gap is the lack of an explicit pointer to the query_video_generation sibling for the retrieve-results step of the workflow, which would complete the agent's mental model for this async operation.

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% and the schema itself is exceptionally rich, documenting per-parameter constraints, modes, and mutual exclusions (e.g., '不能与参考素材混用' for input_image_path, defaults per model, maxItem counts). The description adds model-level context (BYOK billing, endpoint) but no per-parameter meaning beyond the schema. Baseline 3 is appropriate given full 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 states a specific verb+resource: 'submit an async video generation task, immediately return task_id'. It clearly differentiates from the sole sibling query_video_generation by framing the submission action vs. (implicitly) querying. An agent can immediately grasp what this tool does and how it relates to the sibling.

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 BYOK billing context ('直接官方 POST /v2/video_generation，按 API Key 计费，不走订阅额度') gives clear financial/usage context that helps an agent decide when this tool is appropriate. The explicit '提交失败不要自动重试' instruction adds operational guidance. However, it never explicitly names the query_video_generation sibling as the follow-up step for retrieving results, relying instead on inference from the async + task_id phrasing.

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