analyze_image

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It reveals that the tool uses Gemini Vision AI and accepts local paths or URLs, but it does not disclose the return format, network dependency, file size limits, or privacy implications. An agent needs more context to anticipate side effects and output shape.

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, front-loaded sentence with no unnecessary words. Every element—verb, resource, input types, and model provider—is useful and helps the agent quickly understand and select the tool.

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 moderately complex image analysis tool with no annotations and no output schema, the description covers the core capability and input forms but omits output format, supported file types, size limits, and network behavior. It is adequate for basic invocation but not fully complete for an agent that needs to anticipate results and constraints.

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% for all four parameters, so the schema already explains the model, prompt, image_url, and image_path in detail. The description's mention of 'file path lokal atau URL' loosely maps to the image_path and image_url parameters, but it adds no additional semantic meaning beyond what the schema already provides. Baseline 3 is appropriate.

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 uses a specific verb ('Menganalisis dan mendeskripsikan') and identifies the resource ('gambar' / image), explicitly naming the supported input types (local file path or URL) and the underlying model (Gemini Vision AI). This clearly distinguishes it from the sibling tool get_usage_stats, which has a completely different purpose.

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 implies usage for image analysis and description by naming the input types, but it does not provide explicit when-to-use or when-not-to-use guidance, nor does it reference the sibling tool as an alternative. The sibling is distinct enough that confusion is unlikely, but the description itself offers no usage rules beyond the obvious.

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