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

The description discloses that the tool is state-changing, consumes AI credits, creates a generation, and only returns commented code after authorization. This goes beyond the annotations by explaining side effects and prerequisites.

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 concise and front-loads the primary use case. The final 'Use browser guidance for file uploads' sentence is a minor extraneous addition that does not clearly connect to the core behavior.

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?

With no output schema, the description appropriately states that it returns commented code after authorization and notes credit consumption. It is complete enough for an agent, though authorization details are not elaborated.

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?

The schema already fully describes all three parameters with clear descriptions, so the description adds little extra semantic value. It does not elaborate on how filename affects behavior beyond identifying the file 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?

The description clearly identifies the action (adding inline comments, docblocks, docstrings, or annotations) and the resource (user-supplied source code), with explicit trigger language. This distinguishes it from related documentation/test-generation tools even without naming them.

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?

It provides an explicit 'Use this when...' trigger covering the relevant user requests. However, it does not explicitly contrast with sibling tools such as generate-code-documentation or generate-code-tests, leaving some alternative-selection nuance implicit.

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