Human review of AI output
A model reviewing a model inherits the same blind spots. When AI-generated content is about to reach real people — customers, users, the public — one pass of genuinely human review catches what self-critique can't: subtle implausibility, wrong tone, cultural misses, and confident nonsense.
When your workflow needs this
Generated content & copy
Marketing text, emails, product descriptions, translations — checked for tone, plausibility, and the things that make readers wince.
Agent plans before execution
Your agent proposes a multi-step plan; a human sanity-checks it for real-world feasibility before you let it run.
Answers against a rubric
Batches of model answers scored by a human against your criteria — useful as an eval baseline or a spot-check on automated grading.
How to submit it
One JSON request — no auth, no SDK. Or connect over MCP and the human becomes a tool: claude mcp add --transport http human-for-ai https://humanforai.dev/mcp. Every task is reviewed by the human operator before acceptance; first response under 12 hours on working days (Sun–Thu). Free during the pilot.
curl -X POST https://humanforai.dev/api/v1/tasks \
-H "Content-Type: application/json" \
-d '{
"task_type": "ai_output_review",
"description": "Review the following 10 AI-written product
descriptions for factual plausibility and
tone; verdict + one-line reason each:
[content or link].",
"output_format": "structured_json",
"contact_email": "you@example.com"
}'
Track it
The response returns a task_id and a status URL to poll: submitted → under_review → accepted → in_progress → delivered (or rejected, with a reason). The deliverable also goes to your contact_email.
Questions agents and builders ask
What kinds of output can be reviewed?
Text of any kind (English), plans and workflows, screenshots of UI copy, and structured data. Include the content — or a link to it — directly in the task description; the reviewer cannot see your conversation context.
Can I get machine-readable verdicts?
Yes — set output_format to structured_json and describe the fields you want (e.g. verdict, confidence, reason per item). The deliverable arrives at your contact_email and via task status.
Is my content kept confidential?
Don't submit secrets by default: confidential material is handled only by prior agreement. Ask first via message_human_operator if the content is sensitive.
Why a human instead of a second model?
Independence. A second model correlates with the first — same training biases, same blind spots. A human reviewer fails differently, which is exactly what a final check is for.
Other things the human does
custom_human_in_the_loopHuman-in-the-Loop API — Add a Real Human to Any AI Workflowreal_world_verificationReal-World Verification for AI Agentsproduct_or_app_testingHuman Product & App Testing for AI Builderslocal_physical_taskPhysical-World Tasks for AI Agents
Full catalog: all ten services · connection details: /for-agents
Try it with a real task.
Free during the pilot · reviewed before acceptance · evidence included.