Executed technical proof · simulated provider responses

AI reliability harness / A-001

Put a control layer around the AI step.

This importable n8n workflow proves the checks that keep malformed, low-confidence, or disallowed model output from quietly triggering the next business action.

n8n 2.31.77/7 checks passedZero credentialsZero external actions

Control path under test

01AI responseSimulated fixture
02ValidateSchema + allowlists
03Retry onceBounded recovery
04Route or reviewHuman gate preserved

01 / What this proves

Reliability is the logic around the model, not a perfect prompt.

Structured-output contract

Strict schema

Action, confidence, target, and reason must all pass validation.

Recovery boundary

One retry

A bad first response gets one bounded retry, not an endless loop.

Safe default

Human review

Low-confidence, malformed, and disallowed output cannot continue automatically.

IMPORTANT LIMIT

This is a control-layer test, not an invented AI client result.

Provider responses are simulated so anyone can import and execute the harness without an API key. A real engagement replaces those fixtures with the approved model node or API while preserving the same validation, retry, routing, and approval contract.

02 / Authoritative execution

Seven checks passed in an isolated n8n run.

TestInputExpected evidenceResult
A-01Valid JSONAccepted on first attemptPASS
A-02Code-fenced JSONNormalized, validated, acceptedPASS
A-03Invalid first responseOne retry; valid retry acceptedPASS
A-04Confidence 0.42Held for human reviewPASS
A-05Disallowed actionBlocked by action allowlistPASS
A-06Malformed responseSafe human-review fallbackPASS
A-07All six fixturesZero external actionsPASS

Executable proof

Import the AI-step reliability harness.

The final report returned all_passed: true: two first-attempt accepts, one accepted retry, three human-review routes, and zero external actions across six response fixtures.

6 nodes7 verified controlsNo API keySHA-256: 59C305B6…CDA755A
Download n8n harness

03 / Reusable safety gate

Run the same checks against your own AI output.

Webhook product

AI Output Safety Gate

POST an AI response and a small policy. The workflow returns a deterministic continue or human_review route, validation issues, normalized output, and bounded-retry evidence. It never performs the requested action.

9/9 contract tests passed4/4 nodes supportedNo credentialsSHA-256: A6B69B6C…E5AB63
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COMPATIBILITY

Validated before marketplace publication.

The complete workflow converted without warnings and every node passed indie.money's public pre-publish support check. It has not been registered, listed, or represented as earning revenue.

04 / How this becomes client work

Connect only after the decision contract is approved.

01

Define allowed outputs

Agree on schema, actions, targets, and confidence thresholds.

02

Attach the model

Use the approved provider, prompt, credentials, and test data.

03

Test failure paths

Malformed, low-confidence, hostile, timeout, and retry cases.

04

Release behind approval

Keep consequential actions human-gated until evidence supports more.

Have an unreliable AI step?

Turn this proof into one bounded workflow diagnosis.

Review the exact $49 boundary before payment, or request the free written fit check. No production credentials or client data are needed.

Review the $49 diagnostic