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

Annotations mark this as a non-read-only, non-idempotent action, and the description adds the crucial economics (spends credits per picture), the async contract (returns a job; result links the picture and shows a thumbnail inline), and the quote guard that makes the call a no-op without a quote. This goes well beyond the annotation surface.

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, front-loaded sentences that lead with what the tool produces and end with the prerequisite. No filler, though the second sentence packs pricing, workflow, and fallback behavior in a way that takes a second read.

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?

Covers prompt, references, cost, the quote prerequisite, and the asynchronous job return with inline preview, which is strong given no output schema. It could name the job-polling siblings (ugcfans_get_job / ugcfans_wait_job) to complete the async loop.

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 reinforces the quote parameter's behavior and mentions the reference option, but adds little syntax or format detail beyond what the schema already documents.

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 a specific verb and resource ('Makes a picture from a prompt'), plus scope details (optional reference pictures, job-returning). It is clearly distinguishable from siblings like ugcfans_make_video or ugcfans_make_speech, which produce other media types.

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 orders the workflow: call ugcfans_estimate first and pass its quote, otherwise the call returns the cost and makes nothing. It also routes to ugcfans_list_models for pricing, naming concrete alternatives rather than implying them.

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