AI texture / image

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

Goes well beyond annotations by disclosing the async contract (returns a generation id, poll get_generation), the credit cost with automatic refund on failure, and a ~60 s expected duration. Annotations only declare write/openWorld/idempotent/destructive hints; the description adds the operational behavior an agent needs.

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 sentences, front-loaded with purpose and use cases, then exclusions, then async/credit/time behavior. No filler; every clause carries decision-relevant information.

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 purpose, exclusions, sibling routing, async polling, cost/refund, and latency for an 8-parameter write tool with no output schema. Nothing essential to a correct invocation is missing.

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 88%, so the schema already documents model, prompt, image_url, max_credits, aspect_ratio, and idempotency. The prose only loosely reinforces image_url ('optionally from a reference image') and adds no detail on model selection or resolution. Baseline 3 is appropriate when the schema carries the semantics.

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?

Specific verb+resource ('One AI image from a text prompt') with concrete output categories (sprites, flipbooks, emissive/UI textures, concept images) and explicit exclusion of a sibling ('No PBR maps: use pbr-material'). An agent can distinguish this from generate_pbr_material and generate_hdri without opening schemas.

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?

Gives clear when-to-use (sprites, flipbooks, emissive/UI, concept images) and when-not (PBR maps, redirecting to pbr-material), plus the polling alternative get_generation. It omits the quote_generation prerequisite from the prose, though that lives in the max_credits schema description.

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