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Cicd Pipeline Qe Orchestrator

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proffesor-for-testing
cicd-pipeline-qe-orchestrator

Orchestrate quality engineering across CI/CD pipeline phases. Use when designing test strategies, planning quality gates, or implementing shift-left/shift-right testing.

Overview

Publisherproffesor-for-testing
Repositoryagentic-qe
Skill namecicd-pipeline-qe-orchestrator
Stars
480
Forks
92
Bundled files
6
LicenseMIT
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.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by proffesor-for-testing on GitHub. Read the source before you install it.

Installation

Install the Cicd Pipeline Qe Orchestrator 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/proffesor-for-testing/agentic-qe.git /tmp/agentic-qe
mkdir -p .claude/skills
cp -r /tmp/agentic-qe/assets/skills/cicd-pipeline-qe-orchestrator .claude/skills/cicd-pipeline-qe-orchestrator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cicd Pipeline Qe Orchestrator 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 Cicd Pipeline Qe Orchestrator 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 Cicd Pipeline Qe Orchestrator 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.

CI/CD Pipeline QE Orchestrator

<default_to_action> When orchestrating quality across CI/CD pipeline:

  1. ANALYZE pipeline phases: commit, build, test, staging, production
  2. SELECT optimal skills and agents for each phase
  3. CONFIGURE quality gates with measurable thresholds
  4. EXECUTE with parallel agent coordination
  5. ADAPT strategy based on risk, complexity, and environment

Quick Phase Selection:

  • Commit (Shift-Left) → TDD, code review, unit tests
  • Build → Coverage analysis, mutation testing, flaky detection
  • Integration → API contracts, performance, security
  • Staging → Chaos testing, visual regression, accessibility
  • Production (Shift-Right) → Synthetic monitoring, RUM, compliance

Critical Success Factors:

  • Quality gates block bad deployments
  • Agents coordinate through memory namespaces
  • Adapt strategy based on risk level </default_to_action>

Quick Reference Card

When to Use

  • Designing pipeline test strategies
  • Implementing quality gates
  • Coordinating multiple QE agents
  • Shift-left and shift-right testing

Phase-Agent Matrix

PhasePrimary AgentsKey Skills
Commitqe-test-generator, qe-requirements-validatortdd-london-chicago, shift-left
Buildqe-test-executor, qe-coverage-analyzer, qe-flaky-test-huntertest-automation, mutation-testing
Testqe-api-contract-validator, qe-performance-tester, qe-security-scannerapi-testing, performance, security
Stagingqe-chaos-engineer, qe-visual-tester, qe-deployment-readinesschaos-engineering, accessibility
Prodqe-production-intelligence, qe-quality-analyzershift-right, compliance

Quality Gate Thresholds

PhaseMetricThresholdBlocking
CommitUnit coverage> 80%Yes
BuildAll tests pass100%Yes
BuildMutation score> 70%No
TestAPI contractsNo breaking changesYes
Testp95 response< 200msYes
TestSecurity critical0Yes
StagingDeployment readiness> 85%Yes

Fleet Configuration

  • Topology: hierarchical
  • Max Agents: 10 per phase
  • Coordination: aqe/* memory namespace

Pipeline Phases

Phase 1: Commit (Shift-Left)

Goal: Catch defects early, ensure testability

Agents:

  • qe-test-generator - Generate unit tests
  • qe-requirements-validator - BDD scenarios, INVEST criteria

Skills: shift-left-testing, tdd-london-chicago, code-review-quality

javascript
// Parallel execution
Task("Generate Tests", "Create unit tests for new methods", "qe-test-generator")
Task("Validate Requirements", "Check BDD scenarios", "qe-requirements-validator")

Gates: Unit coverage > 80%, Static analysis clean, Code review approved


Phase 2: Build

Goal: Validate integration, ensure coverage

Agents:

  • qe-test-executor - Run test suites
  • qe-coverage-analyzer - Coverage gaps (O(log n))
  • qe-flaky-test-hunter - Detect/stabilize flaky tests
  • qe-regression-risk-analyzer - Minimal regression suite

Skills: test-automation-strategy, mutation-testing, regression-testing

javascript
Task("Execute Tests", "Run full suite, store in aqe/test-results/*", "qe-test-executor")
Task("Coverage Analysis", "Identify gaps", "qe-coverage-analyzer")
Task("Flaky Detection", "Analyze test history", "qe-flaky-test-hunter")

Gates: All tests pass, Coverage > 90% critical paths, No new flaky tests


Phase 3: Integration/Test

Goal: Validate contracts, performance, security

Agents:

  • qe-api-contract-validator - Breaking changes detection
  • qe-performance-tester - Load test critical paths
  • qe-security-scanner - SAST/DAST scans
  • qe-test-data-architect - Realistic test data (10k+/sec)

Skills: api-testing-patterns, performance-testing, security-testing

javascript
// Parallel testing
Task("API Contracts", "Validate for breaking changes", "qe-api-contract-validator")
Task("Performance", "Load test 1000 users", "qe-performance-tester")
Task("Security", "SAST/DAST scan", "qe-security-scanner")

Gates: No breaking API changes, p95 < 200ms, No critical vulnerabilities


Phase 4: Staging

Goal: Validate production-like environment, resilience

Agents:

  • qe-chaos-engineer - Fault injection
  • qe-visual-tester - Visual regression
  • qe-deployment-readiness - Risk assessment

Skills: chaos-engineering-resilience, accessibility-testing, visual-testing

javascript
Task("Chaos Testing", "Controlled failure injection", "qe-chaos-engineer")
Task("Visual Testing", "Visual regression", "qe-visual-tester")
Task("Deployment Check", "Risk assessment", "qe-deployment-readiness")

Gates: Chaos tests pass, No visual regressions, Readiness > 85%


Phase 5: Production (Shift-Right)

Goal: Monitor real usage, validate compliance

Agents:

  • qe-production-intelligence - Incident → test scenarios
  • qe-quality-analyzer - Quality metrics and trends

Skills: shift-right-testing, compliance-testing

javascript
Task("Production Intelligence", "Convert incidents to tests", "qe-production-intelligence")
Task("Quality Analysis", "Production metrics", "qe-quality-analyzer")

Gates: Synthetic monitors pass, Error rate < 0.1%, Compliance validated


Complete Pipeline Example

javascript
// Phase 1: Commit
Task("TDD Generation", "Generate tests for new features", "qe-test-generator")
Task("Requirements", "Validate BDD scenarios", "qe-requirements-validator")

// Phase 2: Build
Task("Execute Tests", "Full suite with coverage", "qe-test-executor")
Task("Coverage", "Analyze gaps", "qe-coverage-analyzer")
Task("Flaky Hunt", "Stabilize flaky tests", "qe-flaky-test-hunter")

// Phase 3: Integration
Task("API Contracts", "Check breaking changes", "qe-api-contract-validator")
Task("Performance", "1000 user load test", "qe-performance-tester")
Task("Security", "SAST/DAST scans", "qe-security-scanner")

// Phase 4: Staging
Task("Chaos", "Fault injection testing", "qe-chaos-engineer")
Task("Visual", "Visual regression", "qe-visual-tester")
Task("Readiness", "Deployment assessment", "qe-deployment-readiness")

// Phase 5: Production
Task("Intelligence", "Convert incidents", "qe-production-intelligence")
Task("Quality Gate", "Final validation", "qe-quality-gate")

Adaptive Strategy

By Risk Level

RiskStrategyAgents
CriticalAll phases, manual gatesFull fleet
HighAutomated gates, comprehensive10+ agents
MediumSmart selection, risk-based5-8 agents
LowMinimal regression, fast2-3 agents

By Application Type

TypeFocus SkillsPrimary Agents
APIapi-testing, contract, performanceapi-contract-validator, performance-tester
Web UIvisual-testing, accessibilityvisual-tester, accessibility
Mobilemobile-testing, compatibilityperformance-tester, visual-tester
Backenddatabase-testing, securitysecurity-scanner, performance-tester

Agent Coordination Hints

Memory Namespace

aqe/pipeline/
├── phase-results/*         - Results from each phase
├── quality-gates/*         - Gate validation results
├── orchestration-plan/*    - Selected skills and agents
├── test-plan/generated     - Test plans
├── coverage/gaps           - Coverage analysis
├── security/findings       - Security results
└── performance/results     - Performance data

Fleet Orchestration

typescript
Task("Fleet Orchestration",
     "Coordinate 10 agents across phases: commit (2), build (3), test (3), staging (2)",
     "qe-fleet-commander")

Blackboard Events

EventTriggerSubscribers
phase:commit:completeCommit phase donebuild agents
coverage:gap:detectedGap foundtest-generator
security:finding:criticalVulnerabilityquality-gate
quality:gate:evaluatedGate decisionfleet-commander

Quality Gate Configuration

json
{
  "commit": {
    "gates": [
      { "metric": "unit_coverage", "threshold": 80, "blocking": true },
      { "metric": "static_analysis_critical", "max": 0, "blocking": true }
    ]
  },
  "build": {
    "gates": [
      { "metric": "all_tests_passed", "threshold": 100, "blocking": true },
      { "metric": "mutation_score", "threshold": 70, "blocking": false }
    ]
  },
  "integration": {
    "gates": [
      { "metric": "api_breaking_changes", "max": 0, "blocking": true },
      { "metric": "performance_p95_ms", "threshold": 200, "blocking": true },
      { "metric": "security_critical", "max": 0, "blocking": true }
    ]
  }
}

Troubleshooting

IssueCauseSolution
OOM during testsRunning all tests in parallelUse batched execution
Pipeline too slowComprehensive testing every commitSmart test selection
Gates always failingThresholds too strictAnalyze trends, adjust

Related Skills


Remember

The CI/CD Pipeline QE Orchestrator provides:

  • Phase-based strategy with optimal skill/agent selection
  • Quality gates that block bad deployments
  • Adaptive strategy based on risk and context
  • Full fleet coordination through memory namespaces

With Agents: Use qe-fleet-commander for multi-agent orchestration. Coordinate through aqe/* memory namespace. Batch operations for efficiency.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Cicd Pipeline Qe Orchestrator AI skill do?

Orchestrate quality engineering across CI/CD pipeline phases. Use when designing test strategies, planning quality gates, or implementing shift-left/shift-right testing.

Why use Cicd Pipeline Qe Orchestrator on TypingMind?

Because you install it once and use it with any model. Cicd Pipeline Qe Orchestrator 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 Cicd Pipeline Qe Orchestrator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/proffesor-for-testing/agentic-qe/tree/main/assets/skills/cicd-pipeline-qe-orchestrator. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Cicd Pipeline Qe Orchestrator?

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 Cicd Pipeline Qe Orchestrator?

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

Is the Cicd Pipeline Qe Orchestrator AI skill free?

Yes. It is published on GitHub by proffesor-for-testing under the MIT 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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