vision_analyze

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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds that it accepts URL or base64 images and returns structured JSON with summary, text, and object list, which is useful behavioral context beyond annotations.

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 compact at three short sentences. Each sentence provides distinct information: what it does, input support, output format, and when to use it, with no wasted words.

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?

The description covers the tool's core inputs and outputs, and annotations supply safety context. While no output schema exists, the return format is summarized. It lacks some edge-case details but is sufficient for a simple, low-risk tool.

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 covers all four parameters with 100% description coverage. The tool description repeats that URL and base64 are supported (image_url/image_data) but adds no extra semantic detail beyond what the schema provides, so the baseline of 3 applies.

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 clearly states the tool's function: analyzing image content. It specifies the resource (images) and action (analyze), and distinguishes itself from sibling tools like vision_chat and audio_transcribe by noting its structured JSON output and one-time analysis nature.

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 notes that it is suitable for one-time image analysis, giving clear usage context. It does not explicitly exclude multi-turn conversations or name alternative tools, but the one-time framing implies a boundary against vision_chat.

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