Apply Review Feedback

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

The description adds valuable behavioral context beyond annotations: it states the tool runs in the background, returns a status of 'pending', and references API key fallback to environment variable. These aspects are not captured in the annotations, which only provide basic hints (read-only, destructive, etc.).

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 well-structured with clear sections for purpose, model selection, arguments, and returns. It is not overly verbose and front-loads the primary action, though it repeats parameter information already present in the schema.

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 covers the key contextual aspects: asynchronous execution, return status, model options, and API key handling. It is sufficiently complete given the output schema and annotations, though it does not mention error conditions or prerequisites beyond the API key.

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 describes all parameters with 100% coverage, so the baseline is 3. The description goes further by explaining the trade-offs between model choices (flash for speed, pro for quality) and clarifying the default, which adds practical semantics beyond the schema's enum list and default values.

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 it applies additional feedback to review results and runs in the background, using a specific verb and resource. However, it does not explicitly distinguish itself from the sibling tool 'blog_apply_feedback', which may serve a similar or overlapping purpose.

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 provides no guidance on when to use this tool versus alternatives. It only explains parameter options (e.g., model selection) but does not mention when to choose this tool over siblings like 'blog_apply_feedback' or 'blog_start_review'.

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