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Dispatch Human to Physical Location

errand_dispatch
Destructive

Send a nearby real human to a physical location for on-site verification, store/shelf/price checks, photos, queue checks or holding, or a pickup. This spends money and creates a real-world action: call errand_quote first, present its exact total_charge_krw, and obtain explicit user confirmation. The worker travels to the site, completes the instructions, and submits GPS/time-verified in-app evidence. Completed tasks pay the worker; failed, expired, or pre-acceptance cancelled tasks refund escrow.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYes
lngYes
titleYesShort worker-facing title, e.g. "성수동 XYZ 팝업 대기줄 확인".
radius_mYesDispatch radius for worker matching.
task_typeYes
reward_krwYes
webhook_urlNoHTTPS URL that receives mission.completed / mission.failed / mission.cancelled / mission.expired events, so you do not have to poll. Payload is advisory — confirm via errand_get_result.
address_hintNoHuman-readable place name/address shown to the worker.
instructionsYesExactly what the worker should do on site, in the worker's language.
report_fieldsNoStructured values the worker must report from the site (e.g. how many people are waiting). Returned in the result and included in the webhook.
expires_in_minutesYes
validation_criteriaYesWhat the photos must show for the evidence to pass, e.g. "매장 입구와 대기줄 전체가 한 프레임에 보여야 함".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already mark destructiveHint=true, but the description adds valuable behavioral context: it spends money, creates a real-world action, requires user confirmation, and describes payment/refund conditions (completed tasks pay worker; failed/expired/pre-acceptance cancelled refund escrow). This goes beyond what annotations provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is four sentences and each conveys necessary information: action/use cases, mandatory quote step, execution/evidence, and financial outcomes. It is slightly dense but front-loaded and without fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (12 parameters, 9 required, no output schema), the description covers the critical workflow and financial consequences. It does not detail all parameter requirements, but the schema covers many, and the description adequately explains the tool's real-world impact.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 58%, so the description carries some weight. It adds general context for reward 'spends money' and location 'nearby real human/physical location', but does not explain specific parameter semantics like task_type options, reward bounds, or expiry defaults, leaving gaps that the schema only partially fills.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the action: 'Send a nearby real human to a physical location' and enumerates use cases (verification, checks, photos, queue, pickup). It distinguishes from siblings by explicitly requiring errand_quote first, which differentiates it from quote/cancel/status tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit prerequisites: call errand_quote first, present its exact total_charge_krw, and obtain explicit user confirmation. However, it does not explicitly state when not to use the tool or name alternative tools for status/result retrieval, so it falls short of a 5.

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

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