ypollak2/llm-router

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

With no annotations provided, the description carries the full burden. It successfully discloses the auto-routing behavior and critical provider-specific constraints (quality is 'DALL-E only'). It could be improved by mentioning rate limits or failure modes, but the provider-specific warnings demonstrate good behavioral transparency.

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 efficiently structured with a single-sentence purpose statement followed by a clear Args list. Every line provides actionable information; there is no redundant text or generic filler. The formatting makes parameter requirements immediately scannable.

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 existence of an output schema (covering return values) and the description's comprehensive handling of the 0%-covered input parameters, the description is appropriately complete. It addresses the complexity of multi-provider routing. A minor gap is the lack of mention of what occurs when model is null (though implied by 'auto-routes').

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?

The schema has 0% description coverage, so the description fully compensates by documenting all four parameters. It adds crucial semantic meaning through concrete examples (e.g., 'gemini/imagen-3', 'openai/dall-e-3', '1024x1024') and value constraints ('standard' or 'hd'), without which the agent would lack guidance on valid inputs.

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 opens with a specific verb ('Generate') and resource ('image'), clearly distinguishing it from text-generating siblings like llm_generate. It further differentiates by specifying the four supported provider families (Gemini Imagen, DALL-E, Flux, Stable Diffusion), establishing clear scope.

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 provides clear context through the 'auto-routes' clause, indicating the tool should be used when automatic provider selection is desired, while the 'model override' parameter implies when to specify a provider manually. While it lacks explicit 'when not to use' exclusions, the auto-routing behavior serves as a functional usage guideline.

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