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

Annotations already declare destructiveHint=true, idempotentHint=true and readOnlyHint=false, so the safety profile is known. The description adds real value beyond them by disclosing the state precondition (must be pending), the irreversible effect on the human, and the non-refund of the ask_human credit.

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 tight sentences with zero filler, front-loading the action and effect before moving to usage conditions and the cost caveat. 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?

Covers purpose, preconditions, usage triggers, and the cost consequence for a destructive one-parameter tool with full schema coverage and no output schema. The only minor gap is that it does not describe what a caller receives on success or failure.

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% and the single question_id parameter is fully documented in the schema as coming from ask_human. The description adds no syntax or sourcing detail beyond that, so the baseline 3 applies.

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 (withdraw) on a specific resource (a still-pending question) and names the effect (the human can no longer answer it). Combined with the references to ask_human, it is clearly distinguishable from the sibling question 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?

Provides explicit when-to-use conditions: the human answered another way, the task changed or was dropped, or a corrected version is about to be asked. It also states the hard precondition ('Only works while the status is "pending"'), which is exactly the routing information an agent needs.

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