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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively conveys that this is a read-only inspection operation revealing viewable images, and indicates the downstream resolution step. However, it doesn't disclose return format details, whether images are embedded or referenced, or any performance/complexity considerations for a detail-fetch operation.

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 compact two-sentence block that front-loads the purpose and immediately follows with actionable workflow guidance. Every sentence serves a purpose—the first states what it does and what you get, the second explains the inspection workflow and next step. No wasted words, though slightly denser than the tightest possible phrasing.

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?

The description adequately covers the tool's purpose, return value (images you can view), and workflow placement for a simple single-parameter detail-fetch tool. The reference to sibling tools adds helpful context. However, given no output schema and no annotations, it could benefit from noting what distinguishes this detail view beyond the images (e.g., whether metadata like scores or explanations are included) to be fully complete.

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% with a single parameter (review_id), and the schema itself documents it as 'Review id from list_visual_reviews,' which precisely describes the source. The description reinforces the source relationship by referencing list_visual_reviews. Since there is only one simple parameter already well-documented in the schema, the description adds appropriate but minimal additional value.

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 tool gets full detail for one AI Visual Review candidate, specifically listing the actual baseline, live, and diff images viewable directly. It explicitly distinguishes from list_visual_reviews (which lists candidates) and names resolve_visual_review as the follow-up decision tool, establishing clear differentiation among the sibling tools.

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 clearly indicates when to use this tool ('use this to inspect a candidate and form your own verdict') and connects it to the follow-up action of calling resolve_visual_review. While it doesn't explicitly state when NOT to use it or name alternatives, the workflow context (inspect then resolve) provides strong practical guidance for appropriate usage.

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