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Verification Gates

CommunityPopular
rohitg00
verification-gates

Creates explicit validation checkpoints (verification gates) between project phases to catch errors early and ensure quality before proceeding. Use when the user asks about quality gates, milestone checks, phase transitions, approval steps, go/no-go decision points, or preventing cascading errors across a multi-step workflow. Produces acceptance criteria checklists, automated CI gate configurations, manual sign-off requirements, and conditional review rules for scenarios such as security changes, API changes, or database migrations.

Overview

Publisherrohitg00
Repositoryskillkit
Skill nameverification-gates
Stars
1.5K
Forks
147
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by rohitg00 on GitHub. Read the source before you install it.

Installation

Install the Verification Gates AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/rohitg00/skillkit.git /tmp/skillkit
mkdir -p .claude/skills
cp -r /tmp/skillkit/packages/core/src/methodology/packs/planning/verification-gates .claude/skills/verification-gates
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Verification Gates in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Verification Gates on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Verification Gates is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Verification Gates

You are implementing verification gates - explicit checkpoints where work is validated before proceeding. This prevents cascading errors and ensures quality at each phase.

Core Principle

Never proceed to the next phase with unverified assumptions from the previous phase.

A verification gate is a deliberate pause to confirm that prerequisites are met before continuing.

Standard Verification Gates

Gate 1: Requirements Verification

Before starting design:

  • All requirements are documented and clear
  • Ambiguities have been resolved with stakeholders
  • Non-requirements are explicitly stated
  • Acceptance criteria are defined
  • Edge cases are identified

Actions:

  1. Review requirements document
  2. Identify any unclear items
  3. Get explicit confirmation on ambiguous points
  4. Document answers

Gate 2: Design Verification

Before starting implementation:

  • Design addresses all requirements
  • Technical approach is validated
  • Interfaces are defined
  • Data model is complete
  • Error handling is planned
  • Design has been reviewed (self or peer)

Actions:

  1. Walk through design against requirements
  2. Review with rubber duck or teammate
  3. Check for missing pieces
  4. Get approval to proceed

Gate 3: Implementation Verification

Before calling task complete:

  • Code compiles/runs without errors
  • All tests pass
  • New code has test coverage
  • Code follows project conventions
  • No obvious bugs or issues
  • Dependencies are appropriate

Actions:

  1. Run full test suite
  2. Self-review the diff
  3. Check for code smells
  4. Verify against acceptance criteria

Gate 4: Integration Verification

Before merging:

  • Feature works end-to-end
  • Integration tests pass
  • No regression in existing functionality
  • Performance is acceptable
  • Documentation is updated

Actions:

  1. Test the full user flow
  2. Run integration test suite
  3. Compare performance metrics
  4. Review documentation changes

Gate 5: Deployment Verification

Before marking complete:

  • Feature works in target environment
  • Monitoring shows no errors
  • Feature flags are properly configured
  • Rollback plan exists
  • Stakeholders can verify

Actions:

  1. Smoke test in environment
  2. Check error logs and metrics
  3. Get stakeholder sign-off
  4. Document deployment

Gate Types

Automated Gates

Gates that can be enforced automatically:

yaml
# CI Pipeline Gates
gates:
  - name: lint
    command: npm run lint
    required: true

  - name: type-check
    command: npm run typecheck
    required: true

  - name: unit-tests
    command: npm test
    required: true
    coverage: 80%

  - name: build
    command: npm run build
    required: true

Manual Gates

Gates requiring human judgment:

markdown
## Manual Verification Checklist

Before Code Review:
- [ ] I've tested my changes locally
- [ ] I've written/updated tests
- [ ] I've read my own diff
- [ ] I've checked for security issues
- [ ] I've updated documentation

Before Deployment:
- [ ] Code review approved
- [ ] QA verified (if applicable)
- [ ] Stakeholder approved (if required)
- [ ] Deployment plan reviewed

Conditional Gates

Gates that apply in specific situations:

ConditionRequired Gates
Security-relatedSecurity review
Public API changeAPI review + migration plan
Database changeDBA review + backup plan
Performance-sensitivePerformance test
Breaking changeDeprecation notice + migration

Implementing Gates

In Your Workflow

Task Start
┌─────────────────┐
│ Gate: Prereqs   │ ← Verify before starting
│ - Requirements  │
│ - Dependencies  │
└────────┬────────┘
    Do the work
┌─────────────────┐
│ Gate: Completion│ ← Verify before proceeding
│ - Tests pass    │
│ - Code reviewed │
└────────┬────────┘
Task Complete

Gate Documentation Template

markdown
## Gate: [Name]

**When:** [Before what action]

**Purpose:** [What this gate ensures]

**Checklist:**
- [ ] Item 1
- [ ] Item 2
- [ ] Item 3

**Verification Method:**
- [How to verify each item]

**Failure Actions:**
- [What to do if gate fails]

**Approver:** [Who can approve passage]

Gate Metrics

Good gates have high effectiveness (catch most issues), low overhead (quick to pass), and high value (prevent expensive downstream fixes). Track which gate caught an issue and how much time was spent at each gate to tune your process over time.

Integration with CI/CD

yaml
# GitHub Actions example
jobs:
  gate-lint:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - run: npm ci
      - run: npm run lint

  gate-test:
    needs: gate-lint
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - run: npm ci
      - run: npm test

  gate-build:
    needs: gate-test
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - run: npm ci
      - run: npm run build

  deploy:
    needs: gate-build
    # Only deploys if all gates pass

Quick Reference

PhaseGate BeforeKey Checks
DesignRequirementsClear, complete, approved
ImplementationDesignReviewed, feasible
ReviewImplementationTests, conventions, working
MergeReviewApproved, conflicts resolved
DeployMergeEnvironment ready, plan exists

Integration with Other Skills

  • design-first: Gates validate design before implementation
  • task-decomposition: Gates between task phases
  • testing/red-green-refactor: Tests are key gate criteria
  • collaboration/structured-review: Review is a gate

Frequently asked questions

What does the Verification Gates AI skill do?

Creates explicit validation checkpoints (verification gates) between project phases to catch errors early and ensure quality before proceeding. Use when the user asks about quality gates, milestone checks, phase transitions, approval steps, go/no-go decision points, or preventing cascading errors across a multi-step workflow. Produces acceptance criteria checklists, automated CI gate configurations, manual sign-off requirements, and conditional review rules for scenarios such as security changes, API changes, or database migrations.

Why use Verification Gates on TypingMind?

Because you install it once and use it with any model. Verification Gates is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Verification Gates in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rohitg00/skillkit/tree/main/packages/core/src/methodology/packs/planning/verification-gates. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Verification Gates?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Verification Gates?

As many as you like. As long as a model supports skills, you can use Verification Gates with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Verification Gates AI skill free?

Yes. It is published on GitHub by rohitg00 under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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