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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description's emphasis on 'read-only' slightly repeats annotations. However, it adds valuable details: validates account caps, live worker coverage, and balance, and specifies return fields (reward_krw, platform_fee_krw, total_charge_krw). This goes beyond annotations, especially for a read-only operation, but doesn't cover all behavioral aspects like error conditions or rate limits, which is acceptable given the annotation coverage.

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 two sentences long, front-loads the main verb and resource, and each sentence adds distinct value: the first states what it does and outputs; the second provides an actionable guidance. No fluff. Could be slightly more structured, but it's efficient and clear.

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?

Given the tool's complexity (5 params, no output schema), the description covers the key aspects: what it returns, what it validates (caps, coverage, balance), and the critical workflow step (obtain confirmation). With annotations covering safety and idempotency, and no output schema to define, the description is complete enough for an agent to call correctly. It doesn't need to explain return formats since there is no output schema, and the required parameters are evident.

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 low at 20%, only radius_m has a description. The description compensates by explaining the purpose of the tool and the key output parameters, but doesn't detail each input parameter (e.g., lat/lng meaning, task_type semantics). Since the schema provides clear names and enums, the description adds value by linking parameters to the quote calculation, but could be more explicit about edge cases or how radius_m affects the quote.

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 the tool obtains a read-only quote for sending a human to a real-world location, listing specific task types (check, verification, photo, queue, pickup) and outputs exact amounts. It immediately identifies the tool's purpose as a quote estimator and distinguishes it from siblings like errand_dispatch and errand_check_coverage.

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 clear usage context: use to get a quote before dispatching, and explicitly instructs to present the total and obtain confirmation before proceeding to errand_dispatch. It doesn't explicitly state when not to use it (e.g., for checking coverage only, use errand_check_coverage), but the context of quote vs. dispatch is clear from sibling names.

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