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Iterate Until Verified

Meng ToCommunityCreated by Meng To

  • Skill
  • Meta (authoring, orchestration, planning, memory)
  • Agent tooling
  • MIT
  • No issues found

From the author

Apply a prompt-agnostic execution and verification loop to any substantial task while preserving the original request. Use when the user asks to fan out work, use subagents or independent reviewers, loop until done, benchmark against references, apply a harsh critic, compare candidates blind, improve an existing prompt with verification, or continue until explicit quality gates pass.
— the description by Meng To

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

Iterate Until Verified provides a structured methodology for managing substantial tasks by separating execution from verification. It forces the translation of subjective quality goals into observable acceptance gates, ensures independent review of work, and mandates evidence-based progression. The skill supports two modes: direct execution of a task or the composition of a reusable prompt wrapper that enforces this rigorous workflow for future use.

What it does

  • Extracts a task contract from user requests to define clear deliverables and constraints.
  • Converts subjective quality requirements into an observable acceptance matrix.
  • Decomposes tasks into independent workstreams for efficient execution.
  • Enforces a separation between implementer and verifier roles.
  • Requires evidence-based verification for every quality gate.
  • Generates reusable prompt wrappers for iterative task management.

When to use it

  • When a task requires high precision and multiple quality checks.
  • When you need to ensure work is reviewed by an independent party.
  • When you want to improve an existing prompt by adding a verification loop.
  • When a task involves complex requirements that benefit from a structured, gate-based approach.

Advantages

  • Prevents the implementer from being the sole judge of their own work.
  • Replaces vague quality goals with concrete, observable pass conditions.
  • Ensures the original task remains authoritative throughout the process.
  • Provides a clear, evidence-based audit trail for final deliverables.

Usage examples

“Write a technical report on cloud migration and iterate until verified.”
The agent will define a contract for the report, establish acceptance gates for technical accuracy and clarity, draft the content, and perform an independent verification pass before finalizing.
“Compose a prompt wrapper for my data analysis task using the iterate-until-verified workflow.”
The agent will return a structured prompt template that includes the authoritative task, the iterative process steps, and the final response requirements for your specific analysis.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/mengto/iterate-until-verified/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip iterate-until-verified.zip -d .agents/skills

Documentation by Meng To

Iterate Until Verified

Preserve the task. Strengthen the process around it.

Choose the mode

  • Execute: Complete the original task with the workflow below. Use this mode by default.

  • Compose: When the user asks for an improved prompt rather than the finished work, return a reusable prompt wrapper. Keep the original task authoritative and unchanged inside the wrapper.

Do not silently switch from composing a prompt to executing it.

1. Lock the original task

Extract:

  • outcome and deliverables

  • audience and use case

  • supplied inputs and references

  • constraints, tools, formats, and exclusions

  • authorized actions and protected boundaries

  • explicit definition of done

Treat these as the task contract. Do not replace the subject, invent requirements, relax constraints, expand permissions, or let the verification method become the deliverable.

Ask a question only when a missing answer would materially change the work and cannot be discovered safely. Otherwise, state a reasonable assumption and proceed.

2. Convert ambition into gates

Translate words such as perfect, best, professional, production-ready, or AAA into observable checks. Select only the dimensions relevant to the task:

  • correctness and factual accuracy

  • completeness against the request

  • craft, clarity, and audience fit

  • usability and accessibility

  • robustness, edge cases, and regression safety

  • performance, security, or compliance

  • visual, editorial, or technical fidelity to a supplied benchmark

Create a compact acceptance matrix:

GateVerification methodPass conditionEvidence
Relevant quality dimensionTest, inspection, comparison, or read-backObservable binary conditionCommand, source, screenshot, output, or artifact

Prefer pass/fail conditions over vague scores. A strong reaction such as “wow” may be a useful signal, but it is never the only gate.

3. Decompose and assign

Split the task into the smallest meaningful workstreams with clear ownership, inputs, outputs, and integration boundaries.

  • Fan out only workstreams that are genuinely independent.

  • Keep coupled edits with one owner to avoid racing changes.

  • Give each worker the original task contract and only the context it needs.

  • Require every worker to return an artifact or evidence, not a confidence claim.

  • Keep one integrator responsible for cross-workstream consistency and regressions.

Use subagents or delegated workers when they are available, permitted, and useful. Otherwise, perform the workstreams sequentially while preserving the same ownership boundaries.

4. Separate making from judging

Do not let an implementer be the sole approver of its own work.

Give the verifier:

  • the original task contract

  • the acceptance matrix

  • the candidate artifact

  • the relevant benchmark or source material

Withhold the implementer’s rationale and self-assessment unless the verifier needs them to reproduce a check. Instruct the verifier to find failures first, cite evidence, reject unsupported claims, and return a gate-by-gate verdict.

For blind comparison:

  • anonymize and randomize candidates when practical

  • compare like with like using the same conditions

  • keep the evaluator blind to author or candidate identity, not to the task or rubric

  • do not call a comparison blind when obvious identity cues remain

5. Match proof to the work

Use the strongest verification surface available:

  • Code: focused tests, typechecks, builds, linters, security checks, runtime behavior, and regression tests.

  • Visual work: rendered output at relevant sizes, interaction checks, accessibility checks, and side-by-side comparison with an accessible reference.

  • Research or analysis: primary sources, reproducible calculations, citation checks, and contradiction searches.

  • Writing: factual checks, brief coverage, audience fit, structure, and an editorial pass against representative references.

  • Plans or decisions: constraint coverage, dependency checks, failure scenarios, feasibility, and explicit tradeoffs.

  • External actions: exact target resolution followed by post-action read-back.

Never substitute a self-rating for evidence. Never invent a benchmark, source, test result, screenshot, or blind verdict.

6. Run the loop

Repeat:

  1. Produce or improve the candidate.

  2. Run every applicable gate.

  3. Record pass, fail, or blocked with evidence.

  4. Route each failure to the responsible workstream.

  5. Make the smallest revision that addresses the evidence.

  6. Re-run the failed gate and any affected regression gates.

  7. Integrate only verified work.

Continue while required gates fail and a safe, in-scope action can make meaningful progress. Do not churn on the same approach after repeated failure; change the approach or report the blocker.

7. Stop honestly

Finish only when:

  • every required gate passes

  • the integrated result still satisfies the original task

  • regressions relevant to the changed work have been checked

  • evidence supports the final claims

  • remaining unknowns are disclosed

Stop as blocked when a required gate depends on missing access, unavailable inputs, new authority, or an infeasible constraint. Name the exact blocker and the minimum next action. Do not weaken a gate merely to declare success.

Compose mode template

When returning an enhanced prompt, use this shape:

Use an iterative execution-and-verification workflow around the authoritative task below.

AUTHORITATIVE TASK
<preserve the user's original task here without changing its subject, deliverables, or constraints>

PROCESS
1. Extract the task contract and convert subjective quality language into observable acceptance gates.
2. Decompose independent workstreams and fan them out when delegation is useful and permitted.
3. Keep one integrator responsible for consistency.
4. Assign an independent verifier that sees the task, rubric, candidate, and references—but not the implementer's self-assessment.
5. Verify with task-appropriate evidence. Use anonymized side-by-side comparison when a real comparable benchmark exists.
6. Route failed gates back to the responsible workstream, revise, and re-check affected regressions.
7. Do not finish until every required gate passes or a concrete blocker is proven.

FINAL RESPONSE
Return the deliverable, a concise gate-by-gate evidence summary, and anything still unverified. Do not claim checks that were not run.

Adapt the process to the task. Do not copy domain-specific tools, benchmarks, or quality claims from another prompt unless they apply here.

Completion checks

  • The original task remains authoritative.

  • Subjective ambition became observable gates.

  • Independent work was separated without creating racing edits.

  • Making and judging were assigned to different roles.

  • Benchmarks were real, comparable, and honestly labeled.

  • Failed gates drove revisions.

  • The final claims match the collected evidence.

Files

LICENSE

MIT License

Copyright (c) 2026 Meng To

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

No issues found by our static scan· No issues found

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Attribution and licence

Created by
Meng To
Publisher
Meng To (Community)
Source
MengTo/Skills · agent-skills/codex/iterate-until-verified · commit 5ea1661
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Meng To or Meng To.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download iterate-until-verified.zip