request_annotation

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

No annotations are provided, so the description carries the full burden. It discloses the async nature by directing the agent to wait for feedback, but doesn't explain whether the call blocks, how long it takes, or what happens if no browsers are connected. The workflow warning is useful but incomplete.

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 short sentences with zero waste. The core action is front-loaded, and the follow-up instruction is clear and actionable.

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 one-param initiation tool with no output schema, the description provides adequate context about the workflow. It could mention connection requirements or error handling, but it covers the essential call-and-wait pattern.

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 description coverage is 100%, so the schema already documents the single 'message' parameter. The description doesn't add syntax or format details beyond what the schema provides, so baseline 3 is appropriate.

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?

States a specific verb (send) and resource (prompt to connected browsers asking user to annotate). Clearly distinguishes from siblings like wait_for_browser_feedback by describing the initiation step rather than the waiting step.

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?

Provides clear workflow guidance: after calling this, use wait_for_browser_feedback ONCE, and do not loop. This effectively tells the agent when and how to use the follow-up tool, though it doesn't explicitly state prerequisites like whether a browser must be connected first.

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