detect_objects

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

No annotations are provided, so the description must fully disclose behavior. It reveals the method (Gemini zero-shot) and output scale (0-1000), but does not mention whether the tool is read-only, permissions needed, or any side effects. With annotations absent, more detail would be expected.

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?

Two sentences: the first states the primary action, the second adds the method and output format. No extraneous words, front-loaded, and efficiently structured.

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 presence of an output schema (context: has output schema true), the description does not need to detail return values, but it succinctly describes the output format. It lacks context on supported image formats, error handling, or performance considerations, but covers the essentials. A minor gap prevents a perfect score.

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 has 100% coverage with detailed descriptions for all 3 parameters. The description does not add new parameter information beyond the schema, which is acceptable. Baseline 3 applies because the schema does the heavy lifting.

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 verb 'Detect' and the resource 'objects in an image with bounding boxes'. It distinguishes from siblings like analyze_image and extract_text by specifying the output format (normalized bounding box coordinates) and the method (Gemini's zero-shot detection).

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 object detection but does not explicitly state when to use this tool over alternatives (e.g., analyze_image for general analysis, extract_text for text detection). No guidance on prerequisites or exclusions is provided.

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