count_products

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

With no annotations provided, the description carries the full burden and does disclose the main outputs: per-label counts, per-item boxes with confidence, and an annotated image. However, it does not explain behavioral details such as how the annotate flag switches between inline and by-reference results, how the conf override affects detection, or any error/edge-case behavior.

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 two tight sentences (~20 words) that front-load the primary purpose first and then list the returns. There is no fluff, redundancy, or extraneous detail.

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?

Since an output schema exists, the description need not re-explain return values, and the purpose is clearly stated. However, it lacks usage direction relative to sibling tools and does not clarify parameter behavior, leaving the overall context slightly incomplete.

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?

Given the reported 0% schema description coverage, the description must compensate for the three parameters (image, conf, annotate) but does not explain any of them. It merely alludes to the annotated image output, leaving the meaning and effect of the conf override and annotate flag unexplained.

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 opens with the specific verb+resource pair 'Count products on a shelf photo', which precisely states the tool's core function. This clearly distinguishes it from siblings like read_price_tags and detect_gaps without any ambiguity.

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?

Usage is only implicitly conveyed through the verb 'Count products on a shelf photo' — the agent must infer when to prefer this over sibling tools such as read_price_tags or detect_gaps. No explicit guidance is given on when to choose this tool or when to select an alternative.

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