show_invokeai_models_card

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

No annotations are provided, so the description carries the full burden. It discloses the return format ('ToolResult with PrefabApp card; plain text fallback in content'), which is helpful for understanding what the tool produces. However, it does not mention error handling or behavior for invalid/missing model_type, but for a read-only display tool this is a reasonable level of disclosure.

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 concise and well-structured: a clear first sentence, a 'Return Format' section, and an 'Examples' section. It uses headers to separate concerns, is front-loaded with the main purpose, and every sentence adds value without unnecessary fluff.

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 simple tool with one optional parameter and no output schema, the description is sufficiently complete: it states the return format and provides an example. It could go further by describing what the card includes (e.g., model names, versions), but the essence is captured. The tool's simplicity means the description is nearly complete.

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%: the only parameter, model_type, has a description listing allowed values ('main, lora, vae, controlnet, spandrel_image_to_image'). The description merely says 'a type' and the example uses 'main', adding no new meaning beyond the schema. Baseline 3 applies because the schema already documents the parameter thoroughly.

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 states exactly what the tool does: 'Show installed models of a type as a rich card.' This specifies the verb ('Show'), resource ('installed models'), and output format ('rich card'). It also distinguishes from sibling card tools (e.g., show_invokeai_queue_card, show_invokeai_gallery_card) by focusing on models and including an example.

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 gives an example call (show_invokeai_models_card(model_type="main")) that implies usage, but it does not explicitly state when to prefer this tool over alternatives like invokeai_models (which likely provides a text list). No when/not-to-use guidance or alternatives are mentioned, so the usage context is only implied.

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