get_image_generation_data

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

Annotations already provide read-only, non-destructive, idempotent, and open-world hints. The description adds valuable behavioral context beyond this: it specifies the tool filters to 'only returns images that have generation metadata' and explains the purpose of the 'exclude_used' parameter (skip already-used images). This enhances understanding of the tool's behavior without contradicting 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?

The description is appropriately concise with four sentences. It front-loads the core purpose, adds focused details, and explains key parameters efficiently. There's minimal waste, though the example values for 'requester' could be slightly more integrated into the flow.

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 parameters, 1 required), annotations cover safety aspects, and an output schema exists (so return values are documented elsewhere), the description is reasonably complete. It explains the tool's specialized focus and key parameters, though it could better differentiate from siblings and cover all parameters more thoroughly.

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%, so the schema provides no parameter documentation. The description partially compensates by explaining 'exclude_used: true = skip already-used images' and 'requester: who is requesting (e.g. "pikabu", "telegram").' However, it doesn't cover 'model_id', 'sort', or 'limit', leaving three of five parameters without semantic explanation in the description.

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's purpose: 'Get full generation parameters from top images of a model.' It specifies the resource (top images of a model) and the action (extract generation parameters). However, it doesn't explicitly distinguish this from sibling tools like 'get_top_images' or 'get_model_images', which likely return different data about images.

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 description implies usage context by stating it's 'focused on extracting the best prompts, settings, and LoRA combinations' and 'only returns images that have generation metadata.' This suggests it should be used when detailed generation data is needed. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_top_images' or provide clear exclusions.

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