跳到正文
cccskills
免费在 GitHub 公开

holistic-testing-pact

Apply the Holistic Testing Model evolved with PACTS (Proactive, Autonomous, Collaborative, Targeted, Structured) principles. Use when designing comprehensive test strategies for Classical, AI-assisted, Agent based, or Agentic Systems building quality into the team, or implementing whole-team quality practices.

中文简介正在准备中。当前显示原文说明。

proffesor-for-testing/agentic-qe星标 515(GitHub 515 + cccskills 0)

实测评分 未实测

查看安装方法

包含的文件(1)

  • SKILL.md8.1 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Holistic Testing Model with PACTS Principles

<default_to_action> When designing test strategies or building quality into teams:

  1. APPLY PACTS principles: Proactive (test before bugs), Autonomous (teams own quality), Collaborative (whole-team responsibility), Targeted (risk-focused), Structured (governance, observability, and explainability of agent behavior)
  2. IDENTIFY quadrant focus: Technology-facing (unit, integration, performance) or Business-facing (acceptance, exploratory, usability)
  3. SELECT agents based on PACTS dimension and testing quadrant
  4. IMPLEMENT feedback loops that catch issues in minutes, not days
  5. MEASURE outcomes (bug escape rate, release confidence, agent confidence) not activities (test count)

Quick PACTS Application:

  • Proactive → Design testability into architecture, risk analysis during refinement
  • Autonomous → Devs run tests locally, CI pipeline with no manual gates
  • Collaborative → Three Amigos, QE pairs with dev, shared test ownership
  • Targeted → Risk-based planning, focus on critical flows, kill valueless tests
  • Structured → Governance, observability, and explainability of agent behavior; measure confidence, not trust

Critical Success Factors:

  • Quality is a whole-team responsibility, not a QA phase
  • QA as enablers (build infrastructure, coach), not gatekeepers
  • Fast feedback during development, not after </default_to_action>

Quick Reference Card

When to Use

  • Designing comprehensive test strategies
  • Building quality culture in teams
  • Choosing testing approach for new projects
  • Evolving from sequential QA to concurrent quality

PACTS Principles

PrincipleFocusAnti-Pattern
ProactiveTest before code, design testabilityWaiting for bugs to find you
AutonomousTeams deploy when readyQA as manual gatekeepers
CollaborativeWhole-team quality thinkingQA works in isolation
TargetedRisk-based, high-value testsExhaustive checkbox testing
StructuredGovernance, observability, explainability of agent behaviorBolting agentic AI onto chaos

Holistic Testing Quadrants

QuadrantPurposeExamples
Tech + SupportFast feedbackUnit, component, integration tests
Tech + CritiqueFind limitsPerformance, security, chaos
Business + SupportShared understandingBDD, acceptance tests
Business + CritiqueDiscover unknownsExploratory, usability, A/B

Agent Selection by PACTS + Quadrant

PACTS DimensionAgents
Proactive + Techqe-test-generator, qe-requirements-validator
Autonomous + Techqe-test-executor, qe-coverage-analyzer
Collaborativeqe-fleet-commander (orchestration)
Targetedqe-regression-risk-analyzer, qe-quality-gate
Structuredqe-fleet-commander, qe-quality-gate (governance, observability, explainability)

PACTS in Practice

Proactive: Test Before Bugs

// During API design, ask: "How will we know if this times out under load?"
// Build observability from start
await Task("Risk Analysis", {
  phase: 'refinement',
  question: 'What could go wrong and how will we know?'
}, "qe-requirements-validator");

Autonomous: Teams Own Quality

  • Developers run full test suite locally
  • CI fails fast with clear diagnostics
  • No manual deployment approvals
  • Self-service test environments

Collaborative: Whole-Team Thinking

  • QE attends planning and refinement
  • Three Amigos for every user story
  • Shared ownership of test code
  • Ensemble testing for complex scenarios

Targeted: Test What Matters

// E-commerce checkout? Test thoroughly.
// Admin panel used twice a month? Lighter touch.
await Task("Risk-Based Planning", {
  critical: ['checkout', 'payment'],
  light: ['admin-panel', 'settings']
}, "qe-regression-risk-analyzer");

Structured: Governance, Observability, Explainability

The 5th principle for agentic systems. As agents take on quality work, you need governance (boundaries and guardrails), observability (what agents did and why), and explainability (decisions you can audit). Especially important in regulated industries.

  • We measure CONFIDENCE, not trust — trust is a human feeling; confidence can be mathematically explained.
  • Ships with a playbook + readiness-assessment guide.
  • Anti-pattern: bolting agentic AI onto chaos. Structure first, then automate.
// Make agent behavior auditable and explainable, not a black box
await Task("Agent Governance Review", {
  guardrails: ['scope-boundaries', 'approval-gates'],
  observability: ['decision-traces', 'confidence-scores'],
  explainability: 'every-decision-auditable'
}, "qe-fleet-commander");

From PACT to PACTS

PACT originated with Reuven Cohen (Agentics Foundation) and was adapted to quality engineering by Dragan Spiridonov. PACTS adds a fifth principle — Structured — inspired by DORA's research on AI-assisted delivery and platform-engineering quality measurement. The addition reflects that autonomous, agentic quality work needs governance, observability, and explainability to be trustworthy at scale.


Evolution from Traditional

Old Way (Sequential)Holistic + PACTS (Concurrent)
Dev writes → QA tests → bugs found → fixesTeam discusses what to build and how to test
Slow feedback, finger-pointingFast feedback, shared ownership
Quality as gatekeepingQuality as enabler
QA on critical pathQA builds infrastructure, coaches

Success Signals

  • Features deploy multiple times per day
  • Bug escape rate trending down
  • Team discusses quality naturally
  • Developers write tests without being told
  • Releases are boring (in a good way)

Agent Coordination Hints

Memory Namespace

aqe/holistic-testing/
├── pacts-assessment/*    - PACTS maturity analysis
├── quadrant-coverage/*   - Coverage per quadrant
├── team-metrics/*        - Quality ownership metrics
└── feedback-loops/*      - Cycle time data

Fleet Coordination

const holisticFleet = await FleetManager.coordinate({
  strategy: 'holistic-testing',
  pacts: { proactive: true, autonomous: true, collaborative: true, targeted: true, structured: true },
  agents: [
    'qe-fleet-commander',       // Orchestration
    'qe-test-generator',        // Tech quadrant
    'qe-requirements-validator', // Business quadrant
    'qe-quality-analyzer'       // Metrics
  ],
  topology: 'mesh'
});

Related Skills


Remember

PACTS = Proactive + Autonomous + Collaborative + Targeted + Structured

Quality is built in, not tested in. Teams own quality. QA enables, doesn't gate. Test what matters, skip what doesn't. Govern agent behavior with observability and explainability — measure confidence, not trust. Measure outcomes, not activities.

With Agents: Agents analyze PACTS maturity, recommend quadrant coverage, and coordinate whole-team quality. Use agents to scale holistic thinking while maintaining human judgment.

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

a11y-ally

免费

Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse, generating context-aware remediation, or testing video accessibility. Supports 3-tier browser cascade with graceful degradation.

中文简介正在准备中。当前显示原文说明。

proffesor-for-testing/agentic-qe5152026年10月26日 更新

WCAG 2.2 compliance testing, screen reader validation, and inclusive design verification. Use when ensuring legal compliance (ADA, Section 508), testing for disabilities, or building accessible applications for 1 billion disabled users globally.

中文简介正在准备中。当前显示原文说明。

proffesor-for-testing/agentic-qe5152026年10月26日 更新

Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

中文简介正在准备中。当前显示原文说明。

proffesor-for-testing/agentic-qe5152026年10月26日 更新

Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.

中文简介正在准备中。当前显示原文说明。

proffesor-for-testing/agentic-qe5152026年10月26日 更新

Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.

中文简介正在准备中。当前显示原文说明。

proffesor-for-testing/agentic-qe5152026年10月26日 更新

Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.

中文简介正在准备中。当前显示原文说明。

proffesor-for-testing/agentic-qe5152026年10月26日 更新

查看 proffesor-for-testing 的全部技能

报告此技能的问题