estimate_image_cost

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

Annotations declare readOnlyHint=false, openWorldHint=true, destructiveHint=false, and the description usefully explains why this is a non-read-only operation: it persists a quote with a 10-minute TTL. It also clarifies the non-destructive boundary ('Does not submit generation'). No auth requirements or rate limits are mentioned, but the TTL and the write-but-safe framing add real context beyond the annotations.

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?

Front-loaded with the core purpose and effects, followed by the model-resolution instruction and the boundary statement. Four tight sentences, though the model-selection guidance repeats the model_type theme across two sentences and could be compressed.

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 7-parameter tool with no output schema, the description covers the critical workflow: where model_type comes from, reference limits, quote TTL, prompt binding, and that it does not generate. What the estimate returns is unexplained, but no output schema exists to lean on, so that gap is the main one.

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 coverage is 57%, and the description compensates meaningfully: it tells the agent to source model_type from list_image_models rather than guess, to derive reference limits from the catalog, and that the quote is bound to the exact prompt. It does not address number, quality, aspect_ratio, or image_quality semantics, which the schema only partially 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+resource ('Estimate image credits') plus the key side effect ('save a 10-minute quote bound to the exact prompt'), and explicitly distinguishes itself from its generation sibling ('Does not submit generation'). An agent can tell this apart from generate_image and estimate_music_cost/estimate_video_cost without opening a schema.

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 a concrete conditional: 'Unless the user specified a model, pass default_model_type from list_image_models,' naming the sibling tool to consult. It also directs the agent to take the model's operation and reference limits from that catalog. It stops short of explicitly naming generate_image as the follow-up when the user actually wants to submit, leaving that to inference.

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