vision_analyze

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

No annotations are provided, so the description carries full behavioral burden. It mentions constraints on local paths and a hint about detail levels, but does not disclose side effects (e.g., read-only nature), rate limits, authentication requirements, or the exact return format. For an analysis tool, these omissions leave a significant transparency gap.

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 one-line purpose, a clear bullet list of image sources, and a short practical hint on detail levels. It is front-loaded and avoids unnecessary verbosity, earning a high score.

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?

With five parameters, no output schema, and no annotations, the description omits essential context: there is no explanation of what the tool returns, no detail on json_mode, and no guidance on max_tokens limits. It also does not mention potential error conditions or prerequisites, leaving the tool under-documented for an AI agent.

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?

Despite 0% schema description coverage, the description adds meaningful context for the images parameter by listing allowed source formats, and for detail by explaining low vs. original usage. However, it leaves json_mode and max_tokens unexplained, and prompt is self-explanatory. It only partially compensates for the lack of schema descriptions.

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 a specific action: 'Analyze one or more images with a custom prompt.' It clearly distinguishes this from preset siblings like vision_describe and vision_ocr by emphasizing the custom prompt, making the tool's purpose obvious.

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 practical guidance on image source types and detail levels (low for coarse, original for fine detail), which helps with parameter selection. However, it does not explicitly state when to choose this tool over alternatives like vision_describe or vision_ocr, leaving the usage context implied.

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