Treat deck image

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

Annotations declare readOnlyHint=false, destructiveHint=false, and openWorldHint=false. The description adds critical context: it modifies the image and saves a new attachment, returns a snippet, and warns against duotone on real-colour subjects. This goes beyond annotations, but annotations already establish mutability.

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?

Description is a single dense paragraph, efficient but packed with information. Could be slightly more structured (e.g., bullet points), but it front-loads the main action and follows with guidelines. No wasted words.

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 (5 params, prerequisite step, output snippet), the description covers all essential aspects: prerequisites, process, output format, and reference to the imagery module. The presence of an output schema reduces the need to detail return values.

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 covers 100% of parameters. Description clarifies relationships (e.g., variant defaults to deck's own) and adds context for mode, scrim, and the required upload step. It enhances the schema without repeating it verbatim.

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 description clearly states the tool transforms an image into 'tahta-grade' by cropping to 16:9, applying duotone, grain, and optional scrim. It distinguishes itself from siblings like generate_deck_image and upload_attachment by its specific role as a fallback treat step.

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 states when to use: 'FALLBACK for off-palette or reused images' and when not: 'prefer rich on-palette images raw'. Provides prerequisite: upload with upload_attachment first. Names alternatives: use mode=none for real-colour subjects.

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