Apply Edward de Bono's Six Thinking Hats methodology to software testing for comprehensive quality analysis.

MITAuto-check passedTesting & QA

Install Six Thinking Hats

skills CLI
$ npx skills add proffesor-for-testing/agentic-qe --skill six-thinking-hats -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install proffesor-for-testing/agentic-qe six-thinking-hats --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/proffesor-for-testing/agentic-qe.git skills-src && mkdir -p .claude/skills && cp -r skills-src/assets/skills/six-thinking-hats .claude/skills/six-thinking-hats && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
six-thinking-hats
GitHub stars
494
Token cost
~1.9k tokens
SKILL.md length
462 words
Files
5
Skills in repo
95
Repo updated
First seen
Licence
MIT

At a glance

Apply Edward de Bono's Six Thinking Hats methodology to software testing for comprehensive quality analysis.

  • Works in 4 steps: DEFINE focus clearly (specific testing… → APPLY each hat sequentially (5 min each) → DOCUMENT insights per hat → …
  • Designing test strategies
  • SKILL.md covers Quick Reference Card, Hat Details, Session Templates and Agent Integration, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Six Thinking Hats is an agent skill from proffesor-for-testing/agentic-qe. Apply Edward de Bono's Six Thinking Hats methodology to software testing for comprehensive quality analysis. Use when designing test strategies, conducting test retrospectives, analyzing test failures, evaluating testing approaches, or facilitating testing discussions. Each hat provides a distinct testing perspective: facts (White), risks (Black), benefits (Yellow), creativity (Green), emotions (Red), and process (Blue).

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files (for example `README.md`, `resources/examples/api-testing-example.md` and `resources/templates/solo-session-template.md`).

It sits in Testing & QA, covering Retrospectives, Test strategy and Failing and flaky tests. The repository describes itself as: Agentic QE Fleet is an open-source AI-powered QA/QE platform designed for use with Coding Agents (works best with Claude Code) featuring specialized agents and skills to support… The licence is MIT.

When your agent uses it

  • Designing test strategies
  • Conducting test retrospectives
  • Analyzing test failures
  • Evaluating testing approaches

Example prompts

  • “/six-thinking-hats”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. DEFINE focus clearly (specific testing question)
  2. APPLY each hat sequentially (5 min each)
  3. DOCUMENT insights per hat
  4. SYNTHESIZE into action plan

What it can do on your machine

Read from SKILL.md and the folder at commit 829d030. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown and typescript).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Six Thinking Hats loads about 1.9k tokens when it runs. Until then it costs about 111 tokens; SKILL.md has 462 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~111
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from proffesor-for-testing/agentic-qe at commit 829d030, republished under its MIT licence (© proffesor-for-testing). 462 words, ~1,902 tokens.

Download SKILL.mdSave it as .claude/skills/six-thinking-hats/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
six-thinking-hats
description
Apply Edward de Bono's Six Thinking Hats methodology to software testing for comprehensive quality analysis. Use when designing test strategies, conducting test retrospectives, analyzing test failures, evaluating testing approaches, or facilitating testing discussions. Each hat provides a distinct testing perspective: facts (White), risks (Black), benefits (Yellow), creativity (Green), emotions (Red), and process (Blue).
category
methodology
priority
medium
tokenEstimate
1100
agents
qe-quality-analyzer, qe-regression-risk-analyzer, qe-test-generator
implementation_status
optimized
optimization_version
1
last_optimized
2025-12-03
quick_reference_card
true
tags
thinking, methodology, decision-making, collaboration, analysis
trust_tier
0

Six Thinking Hats for Testing

<default_to_action> When analyzing testing decisions:

  1. DEFINE focus clearly (specific testing question)
  2. APPLY each hat sequentially (5 min each)
  3. DOCUMENT insights per hat
  4. SYNTHESIZE into action plan

Quick Hat Rotation (30 min):

markdown
🤍 WHITE (5 min) - Facts only: metrics, data, coverage
❤️ RED (3 min) - Gut feelings (no justification needed)
🖤 BLACK (7 min) - Risks, gaps, what could go wrong
💛 YELLOW (5 min) - Strengths, opportunities, what works
💚 GREEN (7 min) - Creative ideas, alternatives
🔵 BLUE (3 min) - Action plan, next steps

Example for "API Test Strategy":

  • 🤍 47 endpoints, 30% coverage, 12 integration tests
  • ❤️ Anxious about security, confident on happy paths
  • 🖤 No auth tests, rate limiting untested, edge cases missing
  • 💛 Good docs, CI/CD integrated, team experienced
  • 💚 Contract testing with Pact, chaos testing, property-based
  • 🔵 Security tests first, contract testing next sprint </default_to_action>

Quick Reference Card

The Six Hats
HatFocusKey Question
🤍 WhiteFacts & DataWhat do we KNOW?
❤️ RedEmotionsWhat do we FEEL?
🖤 BlackRisksWhat could go WRONG?
💛 YellowBenefitsWhat's GOOD?
💚 GreenCreativityWhat ELSE could we try?
🔵 BlueProcessWhat should we DO?
When to Use Each Hat
HatUse For
🤍 WhiteBaseline metrics, test data inventory
❤️ RedTeam confidence check, quality gut feel
🖤 BlackRisk assessment, gap analysis, pre-mortems
💛 YellowStrengths audit, quick win identification
💚 GreenTest innovation, new approaches, brainstorming
🔵 BlueStrategy planning, retrospectives, decision-making

Hat Details

🤍 White Hat - Facts & Data

Output: Quantitative testing baseline

Questions:

  • What test coverage do we have?
  • What is our pass/fail rate?
  • What environments exist?
  • What is our defect history?
Example Output:
Coverage: 67% line, 45% branch
Test Suite: 1,247 unit, 156 integration, 23 E2E
Execution Time: Unit 3min, Integration 12min, E2E 45min
Defects: 23 open (5 critical, 8 major, 10 minor)
🖤 Black Hat - Risks & Cautions

Output: Comprehensive risk assessment

Questions:

  • What could go wrong in production?
  • What are we NOT testing?
  • What assumptions might be wrong?
  • Where are the coverage gaps?
HIGH RISKS:
- No load testing (production outage risk)
- Auth edge cases untested (security vulnerability)
- Database failover never tested (data loss risk)
💛 Yellow Hat - Benefits & Optimism

Output: Strengths and opportunities

Questions:

  • What's working well?
  • What strengths can we leverage?
  • What quick wins are available?
STRENGTHS:
- Strong CI/CD pipeline
- Team expertise in automation
- Stakeholders value quality

QUICK WINS:
- Add smoke tests (reduce incidents)
- Automate manual regression (save 2 days/release)
💚 Green Hat - Creativity

Output: Innovative testing ideas

Questions:

  • How else could we test this?
  • What if we tried something completely different?
  • What emerging techniques could we adopt?
IDEAS:
1. AI-powered test generation
2. Chaos engineering for resilience
3. Property-based testing for edge cases
4. Production traffic replay
5. Synthetic monitoring
Show full SKILL.md (174 more words)Show less
❤️ Red Hat - Emotions

Output: Team gut feelings (NO justification needed)

Questions:

  • How confident do you feel about quality?
  • What makes you anxious?
  • What gives you confidence?
FEELINGS:
- Confident: Unit tests, API tests
- Anxious: Authentication flow, payment processing
- Frustrated: Flaky tests, slow E2E suite
🔵 Blue Hat - Process

Output: Action plan with owners and timelines

Questions:

  • What's our strategy?
  • How should we prioritize?
  • What's the next step?
PRIORITIZED ACTIONS:
1. [Critical] Address security testing gap - Owner: Alice
2. [High] Implement contract testing - Owner: Bob
3. [Medium] Reduce flaky tests - Owner: Carol

Session Templates

Solo Session (30 min)
markdown
# Six Hats Analysis: [Topic]

## 🤍 White Hat (5 min)
Facts: [list metrics, data]

## ❤️ Red Hat (3 min)
Feelings: [gut reactions, no justification]

## 🖤 Black Hat (7 min)
Risks: [what could go wrong]

## 💛 Yellow Hat (5 min)
Strengths: [what works, opportunities]

## 💚 Green Hat (7 min)
Ideas: [creative alternatives]

## 🔵 Blue Hat (3 min)
Actions: [prioritized next steps]
Team Session (60 min)
  • Each hat: 10 minutes
  • Rotate through hats as group
  • Document on shared whiteboard
  • Blue Hat synthesizes at end

Agent Integration

typescript
// Risk-focused analysis (Black Hat)
const risks = await Task("Identify Risks", {
  scope: 'payment-module',
  perspective: 'black-hat',
  includeMitigation: true
}, "qe-regression-risk-analyzer");

// Creative test approaches (Green Hat)
const ideas = await Task("Generate Test Ideas", {
  feature: 'new-auth-system',
  perspective: 'green-hat',
  includeEmergingTechniques: true
}, "qe-test-generator");

// Comprehensive analysis (All Hats)
const analysis = await Task("Six Hats Analysis", {
  topic: 'Q1 Test Strategy',
  hats: ['white', 'black', 'yellow', 'green', 'red', 'blue']
}, "qe-quality-analyzer");

Agent Coordination Hints

Memory Namespace
aqe/six-hats/
├── analyses/*        - Complete hat analyses
├── risks/*           - Black hat findings
├── opportunities/*   - Yellow hat findings
└── innovations/*     - Green hat ideas
Fleet Coordination
typescript
const analysisFleet = await FleetManager.coordinate({
  strategy: 'six-hats-analysis',
  agents: [
    'qe-quality-analyzer',        // White + Blue hats
    'qe-regression-risk-analyzer', // Black hat
    'qe-test-generator'           // Green hat
  ],
  topology: 'parallel'
});


Anti-Patterns

❌ AvoidWhy✅ Instead
Mixing hatsConfuses thinkingOne hat at a time
Justifying Red HatKills intuitionState feelings only
Skipping hatsMisses insightsUse all six
RushingShallow analysis5 min minimum per hat

Remember

Separate thinking modes for clarity. Each hat reveals different insights. Red Hat intuition often catches what Black Hat analysis misses.

Everyone wears all hats. This is parallel thinking, not role-based. The goal is comprehensive analysis, not debate.

© proffesor-for-testing, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files in assets/skills/six-thinking-hats of proffesor-for-testing/agentic-qe.

  • SKILL.md
  • README.md
  • resources/examples/api-testing-example.md
  • resources/templates/solo-session-template.md
  • resources/templates/team-session-template.md

Open the folder on GitHubat commit 829d030

Compare with similar skills

Six Thinking Hats next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Six Thinking Hats compared with similar skills
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Handsontable Unit Testinghandsontable/handsontable22k—~1.2kAutomated safety check: PassCustom licence
Test Softwarehashgraph-online/awesome-codex-plugins1.2k—~508Automated safety check: PassApache-2.0
OpenLogi Change VerificationAprilNEA/OpenLogi23k—~1.4kAutomated safety check: PassApache-2.0
Designing TestsCloudAI-X/claude-workflow-v21.4k1 repos~1.5kAutomated safety check: PassMIT

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Questions about Six Thinking Hats

What does Six Thinking Hats do?

Apply Edward de Bono's Six Thinking Hats methodology to software testing for comprehensive quality analysis. Six Thinking Hats is an agent skill from proffesor-for-testing/agentic-qe. Apply Edward de Bono's Six Thinking Hats methodology to software testing for comprehensive quality analysis.

When should I use Six Thinking Hats?

Six Thinking Hats fits situations like: designing test strategies; conducting test retrospectives; analyzing test failures; evaluating testing approaches.

How do I install Six Thinking Hats in Claude Code?

Run `npx skills add proffesor-for-testing/agentic-qe --skill six-thinking-hats -a claude-code`. Or copy the skill folder (assets/skills/six-thinking-hats in proffesor-for-testing/agentic-qe) into .claude/skills/six-thinking-hats in your project. Claude Code loads it when a task matches its description.

How do I install Six Thinking Hats in Codex?

Run `npx skills add proffesor-for-testing/agentic-qe --skill six-thinking-hats -a codex`. Or copy the skill folder (assets/skills/six-thinking-hats in proffesor-for-testing/agentic-qe) into .agents/skills/six-thinking-hats in your project. Codex loads it when a task matches its description.

Can I use Six Thinking Hats in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add proffesor-for-testing/agentic-qe --skill six-thinking-hats -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/six-thinking-hats, .gemini/skills/six-thinking-hats, .github/skills/six-thinking-hats and .opencode/skills/six-thinking-hats in your project.

What does Six Thinking Hats need to run?

SKILL.md names no scripts, command-line tools or credentials: Six Thinking Hats is instructions for the agent only.

Does Six Thinking Hats access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Six Thinking Hats safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Six Thinking Hats use?

Six Thinking Hats is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Six Thinking Hats use?

About 1.9k tokens (SKILL.md is roughly 7.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Six Thinking Hats?

Skills that share tags, products or a category with Six Thinking Hats: Testing Hashql (hashintel/hash, 1.7k stars), Handsontable Unit Testing (handsontable/handsontable, 22k stars), Test Software (hashgraph-online/awesome-codex-plugins, 1.2k stars) and OpenLogi Change Verification (AprilNEA/OpenLogi, 23k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Six Thinking Hats?

proffesor-for-testing (a GitHub user) maintains it in proffesor-for-testing/agentic-qe, which has 494 GitHub stars. The repository holds 95 skills in this directory. The repository was last updated on October 4, 2026.

Source: proffesor-for-testing/agentic-qe on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.