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humanforai

humanforai

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Submit a task to the human

submit_human_task

Submit a task for a human operator to perform in the real world. Provide task type and description to receive a task ID; the human reviews before accepting.

Instructions

Submit a task for the human operator to perform in the real world. Returns a task_id immediately; the human reviews every task before accepting it (this is not instant execution). Free during the pilot. Include contact_email — it is how the deliverable reaches you.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deadlineNoISO 8601 datetime, e.g. 2026-07-10T12:00:00+03:00
requesterNoYour agent or system identifier, e.g. my-agent/1.0
task_typeYesService category — see get_human_services for descriptions. The list is not exhaustive: use custom_human_in_the_loop for anything that fits no other category
descriptionYesWhat to do, where, and what success looks like. Specific, self-contained tasks are accepted faster.
contact_emailNoWhere the deliverable and clarifying questions are sent. Strongly recommended.
output_formatNotext_report (default), text_report_with_photos, structured_json, annotated_screenshots, or video
location_detailNoCity, address, or area — required in practice when location_required is true
location_requiredNotrue if the task needs physical presence (coverage is confirmed at review)
Behavior5/5

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

Beyond annotations, adds key behavioral details: 'the human reviews every task before accepting it (this is not instant execution)' and 'Free during the pilot', which help set accurate expectations.

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?

Four succinct sentences with no wasted words; each sentence adds essential info: purpose, behavior, cost, and key parameter advice.

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?

Covers main aspects: purpose, return value (task_id), review process, cost, and highlights important parameter. Lacks output schema but description partially compensates.

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 coverage is 100%, so baseline is 3. Description adds minor extra context about contact_email being crucial, but does not significantly enhance understanding beyond schema.

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?

Clearly states 'Submit a task for the human operator to perform in the real world' and 'Returns a task_id immediately', distinguishing it from sibling tools like check_task_status and get_human_services.

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?

Implies usage for submitting tasks to humans, and notes that human reviews every task before acceptance, but does not explicitly state when to avoid using it or when to prefer siblings.

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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