generate_image

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

With no annotations, the description carries the behavioral burden and covers the return format ('a URL (or base64)'), the local-download side effect when save_path is set, and the different generation modes. It does not discuss latency, cost, or API-key/endpoint configuration, but those omissions are minor for correct invocation.

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 efficient and front-loaded: purpose, model, and return type first, then triggers, presets, parameter conditions, and two concrete examples. The bilingual trigger list and examples are purposeful rather than filler.

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 an 8-parameter tool with no output schema, the description covers invocation conditions, parameter behavior, return type, and the optional local side effect with examples. A small gap is the lack of explicit routing to video siblings for video requests, but the tool name and 'image' scope make the boundary clear.

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 description compensates by explaining size tiers, ratio use cases, the images parameter's accepted inputs, and save_path's download behavior. It leaves api_key and base_url semantically unexplained, though those are optional infrastructure parameters and all core generation parameters are well covered.

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 concrete action, resource, and model: 'Generate or edit an image with agnes-image-2.5-flash.' It also lists the distinct modes (text-to-image, image-to-image, edit, multi-image compose) and states the return type, making the tool clearly distinguishable from the video-generating siblings.

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?

It provides explicit invocation triggers in both Chinese and English and gives a clear decision rule: pass `images` for image-to-image/compose, omit it for pure text-to-image. It does not explicitly mention the video sibling tools as alternatives or include a when-not-to-use section, so the guidance stops short of a full 5.

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