analyze_image

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

With no annotations provided, the description carries full behavioral disclosure burden. It does disclose two useful traits: automatic type detection and security validations. However, it does not explain what the validations check, whether the operation is read-only, what side effects occur, or what happens on invalid input or failure.

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, tightly worded sentence with no filler. Every phrase contributes: tool behavior, model, auto-detection, and security. It is appropriately front-loaded and easy to parse.

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?

Given the absence of an output schema and annotations, the description should clarify what the analysis returns and what 'analyze' means in practice. It does not. The security and auto-detection details are useful, but the missing outcome/return information makes the tool incomplete for an agent deciding whether and how to invoke it.

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 100%, so the schema already documents all parameters fully. The description adds minimal semantic value beyond the schema, mainly hinting that analysis_type can be auto-detected. This is a small enhancement, not a substantial clarification.

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 an image'), identifies the technology ('Google Gemini AI'), and mentions key behavior ('automatic type detection and security validations'). It is distinct from sibling tools like upload_to_supabase and get_security_status. However, 'analyze' remains somewhat broad—it does not say what kind of output or result the analysis produces.

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?

There is no explicit guidance on when to use this tool versus the siblings, nor when to choose image_url versus image_path. The 'automatic type detection' hint implies the analysis_type parameter can be omitted, but no direct usage context or exclusions are provided.

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