分析图片

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses that the tool makes an external call to Gemini, specifies the default model and env-var override, and mentions the returned text. It does not mention privacy implications of sending images externally or error behaviors, which keeps it from a 5, but it is far more transparent than the typical 'analyze image' stub.

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 a single, well-structured sentence that front-loads the core action and return value. Every clause adds information: the model used, configurability, accepted image formats, and output type. No filler or repetition of the name/title.

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 relatively simple tool with 100% schema coverage and no output schema, the description sufficiently covers what the tool does, what it returns, and the accepted input formats. It lacks explicit notes on failure modes or limits, but given the straightforward nature and complete schema, it is adequate. A 5 would require more detail on edge cases or output structure.

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 coverage is 100%, so the baseline is 3. The description adds little beyond the schema for parameters: it restates image input types that are already in the schema and mentions model configuration that is not a parameter. It does not provide extra semantics for 'prompt' or 'maxTokens' beyond what the schema already states.

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 a specific action ('analyze an image' via Gemini vision model) and the resource being acted upon, distinguishing it from generic 'process' tools. It also specifies the return type (text description/answer), making the purpose unambiguous. Despite no siblings to differentiate from, the verb+resource+output construction earns full marks.

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 clear context on when to use the tool: whenever an image needs to be analyzed, with explicit support for multiple input forms (local path, URL, base64). It does not explicitly state exclusions or alternatives, but with no sibling tools, the lack of alternative comparison is not a major gap. The model override note adds practical usage context.

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