A collection of Claude Code skills and tools for enhanced development workflows.
ai-debate-hub/
βββ skills/ # Claude Code skills
β βββ debate/ # Three-way debate skill
β βββ validation/ # Comprehensive app validation skill
βββ tools/ # Reusable tools and frameworks
β βββ retrospective-learning.md
β βββ RETROSPECTIVE-LEARNING-INTEGRATION-GUIDE.md
β βββ sample/ # Reference implementations
β βββ feature-validation-SKILL.md
β βββ report-template.html
βββ debates/ # Generated debate transcripts
βββ tests/ # Test files
Location: skills/debate/
Purpose: Three-way debates between Claude, Gemini CLI, and OpenAI Codex CLI
Claude is both a participant and moderator, contributing its own analysis alongside other AI advisors. Enables multi-round discussions where all three systems analyze problems independently and converge on recommendations through genuine debate.
Key Features:
- Multi-round debates (1-10 rounds configurable)
- Session persistence across rounds
- Multiple debate styles: quick, thorough, adversarial, collaborative
- Automatic synthesis of perspectives
- Web viewer for debate visualization
Usage:
/debate Should we use Redis or in-memory cache for our session store?
/debate -r 3 -d thorough Review our authentication implementationLocation: skills/validation/
Purpose: CLI-agnostic browser validation with evidence-based reporting.
Discovers routes, elements, and critical flows, then validates them in a real browser with screenshots, redacted snapshots, console/error checks, failed-network grouping, observed outcomes, resumable state, and an HTML report.
Backend strategy:
- Default:
agent-browser - Fallbacks/adapters: project-local Playwright,
playwright-cli, Playwright MCP, Claude/Codex Chrome MCP tools, andbrowser-harness
Usage:
/validate http://localhost:3000
/validate --interactive
/validate --backend agent-browser --mode standard http://localhost:5173
/validate --backend playwright-local --config validation.config.json --mode standard http://localhost:5173
/validate --fresh
/validate --resumeFor deterministic runs, skills/validation/scripts/select-backend.js can recommend the available backend from the target project before execution.
Output: test-manifest/validation-state.json, evidence files under test-manifest/evidence/, and HTML reports under test-manifest/reports/. Project-local Playwright runs may use validation.config.json for route expectations, permission-aware access-denied handling, breakpoints, and extra redaction values.
Location: skills/audit/
Purpose: Multi-skill technical due diligence pipeline for codebase audits.
The bundle includes the audit orchestrator, setup method, hard-stop checks, Tambon hunt, blind-spot walk, 13 domain audits, audit decision handling, fix-prompt generation, and audit-loop iteration.
Install all audit skills by copying the children of skills/audit/ into your active skill root:
cp -r skills/audit/* ~/.codex/skills/
cp -r skills/audit/* ~/.claude/skills/Primary entry points:
audit-orchestrator: full/auditstyle due diligence.audit-loop: audit, roadmap, remediation, rerun, and skill patching loop.audit-fix-generator: produce remediation prompts for individual findings.
Location: skills/project-setup/, skills/project-curate/, skills/project-doctor/, skills/handoff/, skills/skillify/
These are reusable workflow skills:
project-setup: generate or refreshCLAUDE.mdandAGENTS.mdfrom a real codebase.project-curate: tune a project's.claude/directory with targeted rules/skills/agents.project-doctor: read-only audit of project orchestration scaffolding.handoff: write a structured session handoff for clean context transfer.skillify: turn a successful repeated workflow into a reusable skill.
Location: skills/mercadopago-integration/
Purpose: MercadoPago OAuth/payment integration guidance for Supabase/React-style apps.
The repo copy was checked against the installed skill copies; content differences were line-ending-only for the compared files, so the repo version remains the canonical copy.
Location: tools/sample/feature-validation-SKILL.md
Purpose: Reference implementation showing retrospective learning integration
This is an example skill demonstrating how retrospective learning has been integrated into a real-world validation skill. It includes:
- Phase 1: Trigger capture (reads session transcript)
- Phases 2-9: Feature testing workflow
- Phase 10: Retrospective (evidence-based self-evaluation)
Use this as a reference when integrating retrospective learning into your own skills.
Report Template: tools/sample/report-template.html
Location: tools/retrospective-learning.md
Purpose: Enables skills to learn from execution through evidence-based retrospectives
A reusable module that adds self-evaluation and learning capabilities to any skill by:
- Capturing trigger context - Documents why the skill was invoked
- Tracking execution - Records all actions during execution
- Performing retrospectives - Evaluates performance against original intent with session transcript evidence
Key Benefits:
- Skills learn from mistakes through line-cited evidence
- User corrections are documented as lessons
- Skill improvements suggested based on actual execution
- Works with large session transcripts (> 256KB handled correctly)
Features:
- Cross-platform (Windows/macOS/Linux)
- Size-aware transcript reading
- Evidence-based self-assessment
- Skill improvement recommendations
Location: tools/RETROSPECTIVE-LEARNING-INTEGRATION-GUIDE.md
Purpose: Step-by-step guide for adding retrospective learning to your skills
A practical guide showing how to integrate the retrospective learning module into existing skills with minimal changes.
What it provides:
- Copy-paste prompt template for Claude
- Real before/after example (353 β 528 lines, +49%)
- Section-by-section breakdown of what gets added
- Verification checklist to ensure correct integration
- Troubleshooting for common failures (rewrites, missing content)
- Actual diff showing feature-validation integration
Quick Start:
Backup my SKILL.md with timestamp, then apply retrospective-learning.md to it.
CRITICAL:
- Create backup: SKILL.md.backup-{timestamp}
- Modify SKILL.md directly
- DO NOT rewrite existing content
- ONLY add Phase 1 trigger capture + final phase retrospective
- Renumber phases correctly
- Line count should increase ~40-60% (not double)
Use feature-validation-SKILL.md as reference.
[Full Integration Guide β](tools/RETROSPECTIVE LEARNING-INTEGRATION-GUIDE.md)
git clone https://github.com/wolverin0/ai-debate-hub.git
cd ai-debate-hubCopy skills to your Claude Code skills directory:
# Debate skill
cp -r skills/debate ~/.claude/skills/
# Validation skill
cp -r skills/validation ~/.claude/skills/
# Audit bundle
cp -r skills/audit/* ~/.claude/skills/
# Workflow skills
cp -r skills/handoff skills/skillify skills/project-setup skills/project-curate skills/project-doctor ~/.claude/skills/
# Or link instead of copy
ln -s $(pwd)/skills/debate ~/.claude/skills/debate
ln -s $(pwd)/skills/validation ~/.claude/skills/validationDebate skill:
# Basic usage
/debate Should we implement feature X?
# With options
/debate -r 3 -d thorough Review our API designValidation skill:
# Basic usage
/validate http://localhost:3000
# With options
/validate --resume # Resume from previous validation
/validate --fresh # Start freshFollow the [Retrospective Learning Integration Guide](tools/RETROSPECTIVE LEARNING-INTEGRATION-GUIDE.md) to add self-evaluation capabilities to your own skills.
The debate skill generates a web-based viewer for visualizing debates:
cd debates
python -m http.server 8000
# Open http://localhost:8000/viewer.htmlViewer features:
- Side-by-side round comparison (all 3 participants)
- Synthesis view (final recommendations)
- Full chronological transcript
- State/metadata debug view
- Claude Code CLI
- Gemini CLI -
npm install -g @google/gemini-cli - OpenAI Codex CLI -
npm install -g openai-codex
- Running web application (dev server or static site)
- Recommended backend:
agent-browser - Optional backends:
playwright-cli, Playwright MCP, Claude/Codex Chrome MCP tools, orbrowser-harness
- Claude Code (already required for skills)
- Session transcripts must be accessible at
~/.claude/projects/{project-slug}/*.jsonl
- Debate Skill Documentation - Full debate skill usage guide
- Validation Skill - Adapter-based browser validation skill
- Feature Validation Example - Reference implementation with retrospective learning
- Retrospective Learning Module - Technical documentation for the retrospective learning module
- Integration Guide - How to add retrospective learning to your skills
Before integration:
## Phase 1: Analyze Implementation
git diff --name-only HEAD~5
## Phase 2: Plan Test Scenarios
...
## Phase 9: Generate HTML ReportAfter integration (+175 lines, +49%):
## π¨ CRITICAL BLOCKERS
You MUST read session transcript before and after execution
## Phase 1: Analyze Implementation
**π¨ MANDATORY: Identify Trigger Context from Session Transcript**
[80 lines of trigger capture instructions]
git diff --name-only HEAD~5
## Phase 2-9: [Original content, renumbered]
...
## Phase 10: Retrospective & Learning
**π¨ MANDATORY: Read Session Transcript for Evidence-Based Retrospective**
[80 lines of self-evaluation instructions with line citations]Result: Skill now captures why it was invoked, tracks actions, and performs evidence-based retrospectives citing actual transcript line numbers.
Contributions welcome! Areas of interest:
- New debate styles or moderator modes
- Additional skills with retrospective learning integration
- Improvements to retrospective learning module
- Better visualization in debate viewer
- Bug fixes and documentation improvements
To contribute:
- Fork the repository
- Create a feature branch
- Make your changes
- Submit a pull request
MIT License - See LICENSE file for details
- Repository: github.com/wolverin0/ai-debate-hub
- Issues: Report bugs or request features
- Claude Code: anthropics/claude-code
- v1.0.0 - Initial release
- Debate skill with three-way participation
- Auto-healing module and integration guide
- Feature validation reference implementation
- Web-based debate viewer
Built with Claude Code Demonstrating self-improving skills through retrospective learning and collaborative AI debate.