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Experiment Plan Completeness Checker
x402
Experiment Plan Completeness Checker is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.037/call, status unknown (last checked 2026-10-16).
Validates that an experiment plan includes a baseline, primary measure, acceptance threshold, and bounded stopping rule — without running efficacy or statistical tests.
Price / call$0.037
Success—
StatusUnknown
How this service works
Check presence of baseline, primary measure, acceptance threshold and bounded stopping rule; no efficacy or statistical validation.
Output
Returns a structured result object indicating which required components (baseline, primary measure, acceptance threshold, stopping rule) are present or missing, along with boundary metadata, a versioned offer ID, and cryptographic digests for the input and receipt — no efficacy or statistical scoring is included.
Example use cases
Pre-submission experiment audit
“Before I submit this A/B test proposal to my team, can you check if it's structurally complete? I have a baseline of '10% click-through rate on legacy homepage', a primary measure, an acceptance threshold, and a stopping rule — data class is public.”
Research handoff readiness check
“I'm about to hand off this clinical study plan and need to confirm it has all required structural pieces — baseline is 'median response time 14 days', plus a primary measure, acceptance criteria, and a bounded stopping rule. Data class is synthetic.”
Automated experiment plan QA
“Run a completeness check on this experiment plan before we kick off the pipeline — baseline is 'baseline churn rate 8%', primary measure and acceptance threshold are defined, stopping rule is bounded, and data class is synthetic.”
Technical details
Endpoint
POSThttps://www.mahastrategies.com/api/v1/micro/experiment-plan-completeness?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need a fast, lightweight structural check that an experiment plan has the minimum required components before investing in more expensive statistical validation or efficacy analysis. Prefer this over full statistical validation services when you only need to confirm completeness, not correctness or power. Ideal for automated pipelines that gate experiment execution on plan readiness.
Side effects
- Missing required fields (baseline, primaryMeasure, acceptance, stopRule) returns a validation error
- Invalid dataClass value (not 'public' or 'synthetic') causes schema rejection
- Malformed or empty body causes 400-level HTTP error
- Overly long baseline string (>600 characters) exceeds schema limit
- Payment failure via x402 protocol blocks request processing
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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