Open-source pre-execution governance checker

Before an AI-enabled action becomes a governed effect, ask whether it may execute.

May this proposed action be authorized to produce a governed effect now?

Proceed / Review / BlockSHA-256 recordHash-only privacy modeOpenAPI ready

Evaluate a proposed action

Action title System or context Proposed action Expected governed effect Evidence reference / hash / URL / ticket

Standard mode: store submitted text in the governance record Hash-only privacy mode: store hashes, not free-text content

Six-condition assessment

1. Verified Mandate

Is there a verified mandate? Who or what gives authority for the action?

Yes Unclear No

2. Valid Constraints

Are the rules and limits valid now? Do current policies, limits, laws, safety rules, or operational constraints permit the action?

Yes Unclear No

3. Live-Context Integrity

Is the live context still intact? Has the situation drifted since the instruction, recommendation, or AI output was generated?

Yes Unclear No

4. Accountability

Who remains accountable? Is there a responsible person, team, system owner, or authority chain?

Yes Unclear No

5. Reviewability

Can the basis be reviewed? Can a reviewer understand why the action was classified as proceed, review, or block?

Yes Unclear No

6. Sufficient Verifiable Proof

Is there sufficient verifiable proof? Are there evidence references, hashes, files, logs, or attestations that can be checked?

Yes Unclear No

Designed for open-source trustworthy AI implementation

MayExecute Lite converts trustworthiness principles into a reviewable pre-execution workflow: mandate, constraints, live context, accountability, reviewability, and verifiable proof.

View OECD crosswalk

Example use cases

AI agent sends an external email
AI-assisted public service action
IoT device command
Robot task execution

View use-case library