generate_effects

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

With no annotations provided, the description carries the full behavioral burden. It discloses two important traits: execution is asynchronous in the background, and billing is usage-based and postpaid. These add significant value beyond the plain name and 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?

Two short clauses convey purpose, scope, async behavior, and billing with no filler. Every word 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?

The description covers scope, async execution, and billing, but does not tell the agent how to track completion or retrieve results after the asynchronous run. Since there is no output schema, this is a noticeable gap for a background task.

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. It clarifies that episode_id refers to the entire episode, but it does not explain the expected state or prerequisites of the episode, nor any constraints beyond what the schema already states.

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 specifies a concrete action (automatically match) and a clear resource (visual effects for an entire episode). The use of '视觉特效' (visual effects) distinguishes it from the sibling tool generate_sfx (sound effects).

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 indicates episode-level scope: use this tool when visual effects need to be automatically matched for a whole episode. It does not explicitly name alternative tools or state exclusion conditions, which prevents a 5.

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