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HumanTaskAPI

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Verification Is Part of the Product

HumanTask API verifies real-world task completion with structured evidence such as photos, video, timestamps and location data.

Verification

This page exists to define evidence architecture as a product moat. It should answer that intent directly and avoid borrowing generic copy from unrelated HumanTask API pages.

Verification Starts Before the Task

Proof requirements should be chosen at creation time. If the requester waits until after completion to decide what evidence it wanted, neither the worker nor the software has a stable acceptance rule.

Match Evidence to the Decision

Different questions need different proof. Store stock can require a shelf photo and SKU field. Property documentation may need multiple angles. Remote hands may need before-and-after status. More evidence is not automatically better; relevant evidence is.

Separate Observation from Interpretation

A worker can document a visible crack, displayed error code or posted price without deciding engineering cause, legal meaning or insurance liability. Structured tasks should preserve that boundary.

Use Time and Location Carefully

Timestamps and location context can strengthen evidence, but they are not magic guarantees. The system should record available signals honestly and avoid implying stronger certainty than the data supports.

Represent Missing Evidence Explicitly

If a required image cannot be captured, the result should say why. Missing proof, denied access and unavailable targets are distinct outcomes that the caller may handle differently.

Make Evidence Machine-Readable

Media references should be tied to task IDs and checklist fields. Structured answers make it possible for an agent to validate completeness, compare results or trigger the next step without reading a free-form report.

Verification Becomes a Data Asset

As real tasks accumulate, the platform can learn which evidence patterns reduce disputes and which instructions produce reliable results. That operational knowledge is more defensible than a large directory of unverified profiles.

Next Action

For Verification, use this page as the decision point for its specific intent. Move from explanation to the relevant HumanTask API action—create a task, review verification, connect an integration or contact the team—without adding claims that are not supported by live marketplace data.

Page-Specific Focus

The product role of Verification is narrow by design: define evidence architecture as a product moat. That focus should control the CTA, examples, internal links and any data added later.

Future First-Party Content

When the platform has live usage, strengthen Verification with first-party evidence that matches this intent. Replace generic explanation with actual examples, measured outcomes or screenshots only when those artifacts are real.

Conversion Path for Verification

The page should lead to a next action that matches its intent instead of showing every possible CTA. For Verification, the visitor should move toward the most relevant route after understanding define evidence architecture as a product moat. Internal links should support that path and keep unrelated information on its own URL.

Content Maintenance

Review Verification when the product changes one of these related areas: Verification Starts Before the Task, Match Evidence to the Decision, and Separate Observation from Interpretation. Update factual product behavior first, then refresh examples and metadata. Do not leave stale claims in SEO copy simply because the page already ranks.

Frequently asked questions

What does the Verification page explain?

It is designed to define evidence architecture as a product moat.

What is the main HumanTask API principle here?

Proof requirements should be chosen at creation time. If the requester waits until after completion to decide what evidence it wanted, neither the worker nor the software has a stable acceptance rule.

Does this page claim live worker counts or fixed turnaround?

No. Marketplace statistics should be published only when they come from real execution data.

How do AI agents connect to the platform?

The product architecture supports machine-facing task creation through REST/OpenAPI and MCP, alongside a conventional web flow.

What should a visitor do after reading Verification?

As real tasks accumulate, the platform can learn which evidence patterns reduce disputes and which instructions produce reliable results. That operational knowledge is more defensible than a large directory of unverified profiles.

Next step

Put a human on it.

Describe the place, the action and the proof you need. The API and MCP integration are in developer preview.