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

With no annotations provided, the description carries full burden. It discloses the behavioral consequence of 'approve' (changes the approved baseline for future comparisons) and 'reject' (fails the owning replay run). It also states 'Owner-scoped to your account,' revealing access constraints. This is meaningful behavioral context beyond name/schema.

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?

Three clear sentences with zero waste. It front-loads the core action, defines each decision value with consequences, and closes with a scoping note. Every sentence earns its place.

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?

For a simple 3-param tool with 100% schema coverage and no output schema, the description adequately covers the workflow (inspect via get_visual_review first), decision semantics, side effects, and ownership scope. It doesn't explain return values or error cases, which is acceptable for a tool with no output schema and straightforward semantics.

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%, so the description doesn't need to document parameters heavily. The description adds some semantic context around the 'decision' parameter by explaining what approve/reject mean behaviorally. It also implies note is for traceability, matching the schema's 'logged for traceability' line. Baseline 3 is fair for full-schema-coverage with modest value-add.

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 what the tool does: 'Resolve an AI Visual Review candidate' with specific verbs for each decision value. It defines both 'approve' (promotes live capture to new approved baseline) and 'reject' (fails the owning replay run), which is specific and unambiguous. It distinguishes from sibling tools like get_visual_review and list_visual_reviews by being the action-taking counterpart.

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 says this is used 'after inspecting it (via get_visual_review)', giving the prerequisite workflow step. It explains the consequences of each decision clearly. However, it doesn't explicitly state when NOT to use the tool or reference alternative tools beyond the implicit inspection step.

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