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get_pending_reviews

Fetch all submitted tasks pending your review, including proof of work and automated checks, to meet the 24-hour approval deadline.

Instructions

Fetch all submitted tasks currently awaiting your approval decision — the complete pending-review queue in one call.

Each task in the response includes: • proofOfWork — worker's submitted text, image URLs, and video URLs • criteriaCheckResult — automated syntactic check (passed, score 0–100, per-check details) • imageAuthenticityResult — reverse-image-search result (clean / likely_stock / suspicious / skipped)

⚠️ CRITICAL — 24-hour review deadline: once a task reaches 'submitted', you have exactly 24 hours from submittedAt to call approve_task or dispute_task. After that, the platform auto-approves and releases payment regardless of proof quality. Always process this queue promptly.

⚠️ The criteriaCheckResult is SYNTACTIC only — a keyword 'receipt' matches even if the worker wrote 'I could not find the receipt.' You must read the proof text yourself before deciding.

Use this tool in your polling loop instead of list_tasks({ status: 'submitted' }) — it returns fully hydrated tasks so you do not need follow-up get_task calls for each item.

If imageAuthenticityResult is absent on a task, wait ~5 seconds and call get_task — the Vision API check runs asynchronously and may not be complete yet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

Discloses critical behaviors: the 24-hour auto-approval deadline, the syntactic-only nature of criteriaCheckResult, and the asynchronous generation of imageAuthenticityResult. No annotations exist, so description fully handles transparency.

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?

Well-structured with bullet points and visual flags (⚠️). Somewhat lengthy but every sentence adds informational value. Front-loaded with purpose and use-case.

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

Completeness5/5

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

Covers all necessary aspects: what the tool returns, how to interpret the fields, the review deadline, and follow-up actions for incomplete data. Despite no output schema, the description is comprehensive.

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

Parameters4/5

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

No parameters exist, so description does not need to explain them. It adds value by detailing the returned fields, which compensates for lack of output schema. Baseline for zero parameters is 4.

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 the tool fetches all submitted tasks awaiting approval, distinguishing it from list_tasks by noting it returns fully hydrated tasks without needing follow-up calls.

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

Usage Guidelines5/5

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

Explicitly advises using this tool over list_tasks in a polling loop, and provides guidance on handling missing imageAuthenticityResult with a wait and get_task call.

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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