analyze_image

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

No annotations are present, so the description itself must disclose behavioral traits. It does so by explaining the multimodal model's capability versus the agent's text-only limitation, and it details the exact image input formats (path, URL, data URI, clipboard, raw). It also discloses that `prompt` overrides `task`, and that `save_to` returns a path and summary instead of the full description. This goes well beyond a generic 'analyze image' statement, though it omits potential error cases or rate limits.

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 well-structured: a one-sentence summary, a bulleted list of image sources, and short clauses for task/detail/save_to. It avoids redundancy with the schema and every section contributes to understanding. The length is appropriate for a tool with 5 parameters and no output schema.

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 tool with 5 parameters, no output schema, and no annotations, the description covers all essential aspects: the image input formats are fully enumerated, the task/prompt relationship is clarified, detail behavior is stated, and save_to is explained. It also tells the agent what response to expect (text description, or path+summary when saving). There is a small gap around edge cases like invalid image or network issues, but the description is still remarkably complete for its complexity.

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 input schema already documents all five parameters with descriptions, so the baseline is 3. However, the tool description enriches the schema by explaining the meaning and valid values for `image` (the five source options), the distinction between `task` and `prompt`, the default for `detail`, and the file-writing behavior of `save_to`. This is genuinely useful semantic information beyond the schema, justifying a 4.

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 first line states exactly what the tool does: 'Analyze an image using a multimodal model and return a detailed text description.' It also clarifies the vision-model vs text-only agent distinction, giving the agent a clear mental model. No sibling tools to differentiate, so this is as clear as it gets.

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 detailed guidance on how to supply the `image` parameter via five distinct source types, and instructs the agent to pick a `task` or provide a custom `prompt`. It even explains that `task` is ignored when `prompt` is provided, and notes the `detail` default and `save_to` behavior. Since there are no sibling tools, it does not need to distinguish use cases, but it could explicitly state when not to use it (e.g., for non-image analysis). Still, the guidance is clear and actionable.

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