Solution Pack

Verify an AI Output Before You Act

Use a bounded verification loop when an AI answer could influence a consequential message, configuration, purchase, publication or decision.

Use this when

You have an AI-generated answer that looks plausible, but at least one claim matters enough that acting on a confident mistake would be costly.

  • An AI answer is about to influence a real action.
  • The answer contains factual, technical, current or source-dependent claims.
  • You need a repeatable review trail rather than another generated opinion.

Avoid forcing the pack when

  • The task is low-stakes brainstorming where verification would cost more than the decision.
  • The action requires a specialist, formal approval or authority the agent does not have.

What you should leave with

A verification note that separates the decision, decisive claims, independent evidence, failure checks and the final action.

  • Situation and action
  • Method register
  • Verification note
  • Unresolved risk
  • Next action
  • Check / stop / escalation rule

Practise before the real task

Try the judgement before you need it.

A real task may carry consequences. The Academy gives you a safer case to practise on first, with an explanation and a link to the released method. Your practice stays in this browser.

Copy a prompt

Use this pack with your AI

Describe your task, then copy the prompt into your AI assistant. The prompt asks it to check which methods fit, prepare the output shown above and identify what to check next.

Vedokrok keeps this text only while this page is open. If you paste the prompt into an AI service, you share the text with that service.

Preview the prompt

If your AI cannot open the pack link, download the Markdown file and attach it to the same conversation.

Run it level by level

Level 0 — Scope the action

Name the decision, stakes, reversibility and what must be true before acting.

Level 1 — Find decision-critical claims

Reduce a fluent answer to the claims that could change the action.

Methods: MHC-D-RESEARCH-0318

Level 2 — Build independent evidence

Open primary or system evidence with a different failure path and check source fit.

Methods: MHC-D-RESEARCH-0996 · MHC-D-RESEARCH-0494

Level 3 — Test the real result

Run the smallest check that could expose a consequential mistake.

Methods: MHC-D-RESEARCH-1010

Level 4 — Challenge the recommendation

Look for the strongest unresolved failure mode and decide whether to use, test, reject or escalate.

Methods: MHC-D-RESEARCH-0495

Level 5 — Preserve the check

Leave a compact verification note and a reusable regression check when the failure pattern matters.

Methods: MHC-D-RESEARCH-0495

Go deeper only when the core pack leaves a gap.

The methods below are the curated core. A connected agent may search the wider released Vedokrok library only after it finishes the core Method Register and can name a material gap. Expansion is capped at two searches and three supplemental methods, which stay in a separate register so they are not mistaken for pack-curated methods.

Method Register

Inspect every method, then mark it as use, skip or unclear. A skipped method is not a failure; forcing every method would make the pack less trustworthy.

Item ID | version | role | fit: use/skip/unclear | concise reason | evidence/source role | important limit | source URL

Released methods in this pack

Cross-check the fact before the agent acts on it
Identify and cross-check the fact the action depends on. · MHC-D-RESEARCH-0318 · version 0.1.0
Give the second check evidence the first answer did not create
Use evidence the first answer did not create. · MHC-D-RESEARCH-0996 · version 0.1.0
Check that it meets the specification and solves the real problem
Check real usefulness separately from format conformance. · MHC-D-RESEARCH-1010 · version 0.1.0
Do not expose AI confidence until you have tested its calibration
Keep model confidence separate from evidence. · MHC-D-RESEARCH-0494 · version 0.1.0
Keep a list of high-confidence AI failures
Turn dangerous misses into reusable regression checks. · MHC-D-RESEARCH-0495 · version 0.1.0

Take the pack with you

Markdown is the easiest portable form for a chat or agent. JSON is available for tools that want a structured contract. The run record template gives an agent a stable way to preserve its Method Register, artifact and check without exposing private chain-of-thought. Saved files do not update themselves.

Review a run record

Already used this pack with an AI assistant? Paste its run-record JSON or choose a file to read the result, next check and remaining gaps.

This review stays in this open page. Vedokrok does not upload or save the file or text. Copying shares nothing until you paste it elsewhere.

Maximum 128 KiB. Use this pack’s run record with the same pack version and knowledge release.

Selected knowledge release: MHC-RPUB-20261011-9e4b62c5. Check live method pages, current availability and notices before consequential reuse. Pack inclusion is not an efficacy claim or human approval.