inspect_dataset_quality

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

With no annotations, the description carries full burden for behavioral disclosure. It states 'inspect' (read-only implied) but does not clarify side effects, permissions, or whether it modifies any state. The agent cannot determine safety or constraints from this description alone.

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?

Description is very concise (one sentence) and front-loaded with the action, but it lacks necessary detail. While efficiency is good, the trade-off with completeness reduces its overall helpfulness.

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?

Despite having an output schema, the description does not indicate what quality metrics or results are returned. The agent cannot form accurate expectations about the tool's output, making it incomplete for informed tool selection.

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 0% and description adds no meaning for the two parameters (dataset_path, max_images). The agent must rely on the schema alone, which only provides names, types, and defaults. No indication of how max_images affects inspection or the format of dataset_path.

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?

Description clearly states the tool inspects local dataset image quality with a specific temporal context ('before first preview rendering'), which helps differentiate it from related tools like list_quality_profiles or score_dataset_preview_candidates. However, it could more explicitly distinguish itself from siblings.

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?

Implies usage before first preview rendering, but no explicit guidance on when to use this tool versus alternatives (e.g., score_dataset_preview_candidates) or when not to use it. The agent lacks context on prerequisites or exclusions.

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