analyze_image

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

With no annotations, the description discloses the return format (markdown and JSON) and a behavioral trait (treat text as untrusted). It does not cover auth, rate limits, or error scenarios, but the disclosed info is valuable and non-obvious.

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 at 4 sentences, each serving a clear purpose: purpose, usage, rationale, and behavioral note. 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 tool has 6 parameters, no required ones, and an output schema exists but is not described in the description. The description covers main use cases but misses parameter details, error handling, and constraints. It is minimally adequate given the 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?

Schema description coverage is 0%, yet the description adds no per-parameter details. It does not explain the purpose of each parameter like mode, detail_level, or output_format. The mention of 'structured JSON evidence' is too vague to compensate for the lack of parameter semantics.

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?

Clearly states the tool analyzes images for coding agents, listing many specific use cases (screenshots, diagrams, etc.). However, it does not explicitly differentiate from sibling tools like analyze_ui_screenshot or compare_images, missing a chance to clarify boundaries.

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?

Provides explicit when-to-use instructions ('Use this whenever...') and a caution about trusting text. But lacks when-not-to-use guidance or mention of alternatives, such as using analyze_ui_screenshot for UI-specific analysis.

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