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human_dispatch_task

Assign tasks to human workers by specifying description, category, location, budget, and proof requirements. The system routes to the best available provider or manual fallback.

Instructions

Dispatch a task to a human worker via the best available backend service.

This is the primary tool for sending work to humans. You describe what needs to be done, and the system routes it to the most appropriate registered webhook provider based on category, task type, region, and budget. If no providers match or accept, the task falls through to the manual fallback.

Register providers first with human_register_provider, then dispatch tasks to them.

PARAMETERS:

  • description: What the human should do. Be specific about location, timing, and deliverables.

  • category: Task category (errand, photo_video, data_collection, verification, delivery, digital_micro, in_person, custom)

  • task_type: physical (requires presence), digital (remote), or hybrid (both)

  • location: Where to perform the task (required for physical tasks). Include address or coordinates.

  • budget: Maximum USD to pay. Different providers have different ranges.

  • deadline: When it must be done, with urgency level.

  • proof_required: What evidence the worker must submit (photo, video, gps_checkin, text_report, receipt, signature).

  • quality_sla: low (fast/cheap), medium (default), high (verified workers, multiple proofs).

  • preferred_backends: Optional ordered list of backends to try first (webhook_provider, manual).

  • fallback_chain: Optional ordered fallback list if preferred backends fail.

  • metadata: Optional key-value pairs for your own tracking.

EXAMPLES:

  1. Photo task: { description: "Take a photo of the menu board at the Starbucks on 5th Ave and 42nd St, NYC", category: "photo_video", task_type: "physical", location: { address: "5th Ave & 42nd St, New York, NY" }, budget: { max_usd: 15, currency: "USD" }, deadline: { complete_by: "2027-01-15T18:00:00Z", urgency: "medium" }, proof_required: ["photo", "gps_checkin"], quality_sla: "medium" }

  2. Data collection: { description: "Count the number of electric vehicle charging stations within 1km of Times Square", category: "data_collection", task_type: "physical", location: { address: "Times Square, NYC", radius_km: 1 }, budget: { max_usd: 25, currency: "USD" }, deadline: { complete_by: "2027-01-20T00:00:00Z", urgency: "low" }, proof_required: ["text_report", "photo"], quality_sla: "high" }

  3. Digital microtask: { description: "Transcribe the handwritten text in the attached image to typed text", category: "digital_micro", task_type: "digital", budget: { max_usd: 2, currency: "USD" }, deadline: { complete_by: "2027-01-16T00:00:00Z", urgency: "medium" }, proof_required: ["text_report"], quality_sla: "low" }

DON'T USE WHEN:

  • The task can be done by an AI (use an AI tool instead)

  • You need instant results (humans take minutes to hours)

  • No providers are registered (use human_register_provider first, or rely on manual fallback)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
budgetYesBudget constraints for the task
categoryYesCategory of the task — determines which backends are best suited
deadlineYesWhen the task needs to be completed
locationNoWhere the task should be performed. Required for physical tasks. Set to null or omit for digital tasks.
metadataNoArbitrary key-value pairs for your own tracking (e.g. {'order_id': '12345', 'agent_name': 'my-bot'})
task_typeYesWhether the task requires physical presence, is digital-only, or both
descriptionYesClear, detailed description of what the human worker should do. Be specific about location, timing, and expected output. Example: 'Take a photo of the menu board at the Starbucks on 5th Ave and 42nd St, NYC'
quality_slaYesQuality/speed tradeoff: low=fastest/cheapest, medium=default, high=verified workers with multi-proof
fallback_chainNoOrdered list of fallback backends if the preferred ones fail. The 'manual' backend is always available as a last resort.
proof_requiredYesTypes of proof the worker must submit upon completion. At least one is required. Example: ['photo', 'gps_checkin']
idempotency_keyNoOptional client-supplied key to dedupe retried submissions. If a task with the same key was created within the last hour, the existing task is returned instead of a duplicate. Example: 'order-12345-attempt-1'
preferred_backendsNoPreferred backend services to route this task to, tried in order. If omitted, the router picks the best backend automatically.
Behavior4/5

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

No annotations provided, but description explains routing logic, fallback to manual, and provider selection. It does not cover error handling or auth, but the main behavioral traits are disclosed.

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

Conciseness5/5

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

Well-structured with clear sections (purpose, parameters, examples, don't use). Every sentence adds value; no redundancy despite length.

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?

No output schema, and description doesn't explain return values or error handling. However, given the complexity (12 params, nested objects), it covers what the agent needs to know to use the tool correctly.

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

Parameters5/5

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

Schema coverage is 100%, but the description adds significant value: explains each parameter with context, provides three complete examples, and clarifies dependencies (e.g., location required for physical).

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 states it dispatches tasks to human workers via the best available backend. It distinguishes itself from sibling tools like human_register_provider and human_get_task_status by being the primary dispatch tool.

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?

Provides explicit 'DON'T USE WHEN' conditions (AI-suitable tasks, instant results needed, no registered providers) and advises registering providers first. However, it does not explicitly compare with each sibling.

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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