generate_backdrop

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

With no annotations, the description carries full burden for behavior, and it delivers: it discloses that the prompt is rewritten to enforce background-plate rules, that the saved file is locally measured for contrast/clutter/drift/edge seam, that the file is always kept because it is already paid for, and that a FAILED verdict is not an automatic retry. This gives the agent important externally invisible behavior.

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?

The description is well structured and not wasteful: a one-line purpose, a prioritized STOP instruction block, then a plain-language behavior block, then a compact Args list. The all-caps/STOP stands out without being noise, and every sentence adds operational or behavioral value.

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?

Given the tool's complexity (8 params, 4 required, no annotations), the description is complete enough: it explains all parameters, return values (saved path, measurements, PASS/FAILED verdict), failure handling, and important warnings. The presence of an output schema covers shape details, so the description fills the remaining contextual gaps.

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%, but the Args section documents all 8 parameters with concrete examples and caveats: palette accepts an array or single string, seed gives reproducible output, tileable triggers seam measurement, out_dir is created if missing, size is exact dimensions, and model should be omitted by default. This fully compensates for the sparse schema.

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 first sentence states a specific verb and resource: 'Generate a background plate that the project's UI can sit on top of.' The rest of the description scopes the tool further by mentioning background-plate discipline, avoiding text/logos/centre subject, and measuring contrast for overlay text, which clearly distinguishes it from a general image generator like generate_image.

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 STOP block gives strong contextual guidance: read actual project colors before calling, pass them as palette, never invent palette from the prompt, derive overlay_text_color from UI text, avoid seedream models for non-square backdrops, and treat FAILED as a diagnostic rather than a retry trigger. It does not explicitly mention when to prefer generate_image instead, so it misses explicit exclusions/alternatives, but the usage context is clear.

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