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

Beyond the annotations (destructiveHint=true, openWorldHint=true), the description discloses real behavior: it takes a checkpoint first and restores the image on failure or when no product is found, it exports JPEG (PNG only when the background is transparent), and color_strength is auto-eased so strong colors don't clip. The single-layer precondition and amazon-specific overrides further reduce surprise.

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 a one-sentence summary, then dense but information-bearing clauses; almost every phrase carries a default, range, or constraint. It is a long run-on paragraph rather than a structured list, which costs a point but wastes little.

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 10-parameter, no-output-schema tool, the description covers the pipeline, output format, per-marketplace sizing, all option domains, defaults, and failure/rollback behavior. Nothing essential for calling it correctly 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 coverage is 100%, so the baseline is 3, but the description adds cross-parameter meaning the schema does not: amazon forces a white background and disables shadow, gradient_bottom defaults to 15% darker than gradient_top, 'upload:<id>' supplies another photo as background, and fill is bounded 0.5-0.95. These constraint interactions justify a bump above baseline.

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?

Opens with a concrete verb+resource+outcome ('Turn a product photo into a marketplace-ready listing image in one call') and then enumerates the full pipeline it performs (find, cut out, frame, background, shadow, color, export). An agent can distinguish this from generic siblings like export_photo or crop_for_platform without opening the 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 rich selection context: per-marketplace dimensions and constraints, 'amazon allows only white', shadow auto-off for amazon, and the 'image must have a single layer' precondition. It does not, however, explicitly route the agent away from the visually similar siblings (crop_for_platform, export_photo) or say when this tool is the wrong choice.

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