diegosouzapw Wolf Agents Master Skill
This is the master skill that provides access to Wolf Agents' institutional knowledge accumulated over 50+ phases of development. Enhanced with Superpowers Skill-Chaining patterns (Phase 1 & 2) for dramatically improved agent compliance.
What's New in v1.1.0
Phase 1 & 2 Enhancements (November 2025):
- ✅ Explicit Skill Chaining: "REQUIRED NEXT SKILL" callouts forcing sequential workflows
- ✅ Rationalization Blocking: "Red Flags - STOP" sections catching common shortcuts
- ✅ Mandatory Verification: Checklists with pass/fail criteria that cannot be skipped
- ✅ Good/Bad Examples: Concrete compliance patterns (8 example pairs added)
- ✅ Subagent Templates: 4 role templates for easy delegation
- ✅ Extended Coverage: All core skills + wolf-verification integrated
Expected Impact: Agent compliance rates improved from 30-50% to 90-95% across all governance requirements.
Available Wolf Skills
Core Framework Skills (v1.1.0 - v1.2.0)
🚀 wolf-session-init (v1.0.0) START HERE
Master initialization skill with mandatory 4-step protocol
Use when:
- Starting ANY new work or session
- Session recovery after context loss
- Beginning implementation work
Provides:
- BLOCKING gates for principles → archetype → governance → role
- Session initialization checklist
- Context recovery protocol
MCP Tool: Start with this skill, then follow its chain
🎯 wolf-principles (v1.1.0)
Wolf's 10 core principles guiding system design and agent behavior
Use when:
- Making architectural decisions
- Justifying design choices
- Resolving conflicts between priorities
- Understanding Wolf's philosophy
Enhancements:
- Red Flags - STOP section (6 rationalizations)
- Chains to wolf-archetypes
- Verification checklist (5 items)
MCP Tool: mcp__wolf-knowledge__query_principles({ principle_id: 1-10 })
🔄 wolf-archetypes (v1.2.0)
Behavioral archetype selection with overlay lenses
Use when:
- Starting new work items
- Determining priorities and evidence requirements
- Applying specialized quality gates (performance, security, accessibility, observability)
Enhancements:
- Red Flags - STOP section (7 rationalizations)
- 5 Good/Bad example pairs showing proper archetype selection
- Chains to wolf-governance
- Verification checklist (6 items)
MCP Tool: mcp__wolf-knowledge__find_archetype({ labels: [...], description: "..." })
🛡️ wolf-governance (v1.2.0)
Compliance rules, quality gates, and process standards
Use when:
- Checking Definition of Done requirements
- Understanding quality gates (Fast-Lane, Full-Suite)
- Validating PR readiness
- Understanding approval requirements
Enhancements:
- Red Flags - STOP section (8 rationalizations)
- 3 Good/Bad example pairs (feature PR, security change, refactoring)
- Chains to wolf-roles and wolf-verification
- Verification checklist (8 items)
MCP Tool: mcp__wolf-knowledge__search_governance({ query: "quality gates" })
📋 wolf-roles (v1.2.0)
Guidance for 50+ specialized agent roles with responsibilities
Use when:
- Understanding role responsibilities and boundaries
- Determining collaboration patterns
- Identifying escalation paths
- Using subagent templates for delegation
Enhancements:
- Red Flags - STOP section (7 rationalizations)
- 4 subagent templates (coder, pm, security, code-reviewer)
- Subagent delegation patterns
- Verification checklist (6 items)
- Marks completion of primary skill chain ✅
MCP Tool: mcp__wolf-knowledge__get_role_guidance({ role_name: "agent-role" })
✅ wolf-verification (v1.1.0)
Three-layer verification (CoVe, HSP, RAG) for continuous validation
Use when:
- During implementation at checkpoints
- Before claiming work complete
- Validating evidence requirements
- Checking confidence scores
Enhancements:
- Red Flags - STOP section (7 rationalizations)
- 2 Good/Bad examples
- Integration with governance gates
- Verification checklist (6 items)
MCP Tool: mcp__wolf-core-ip__check_confidence({ model_confidence, evidence_count, ... })
Automation & Scripts (v1.1.0)
⚙️ wolf-scripts-core (v1.1.0)
Core automation for archetype selection, evidence validation, quality scoring
Use when:
- Automating archetype selection
- Validating evidence requirements
- Scoring issue quality with curator rubric
- Validating bash scripts
Enhancements:
- Red Flags - STOP section (6 rationalizations)
- 2 Good/Bad examples (archetype selection, evidence validation)
- Integration with wolf-archetypes and wolf-governance
- Verification checklist (5 items)
Scripts: select-archetype.mjs, evidence-validator.mjs, curator-rubric.mjs, bash-validator.mjs
🤖 wolf-scripts-agents (v1.1.0)
Agent coordination, orchestration, and multi-agent workflow management
Use when:
- Coordinating multi-agent workflows
- Enforcing agent file scope boundaries
- Using mailbox system for async communication
- Orchestrating complex pipelines
Enhancements:
- Red Flags - STOP section (6 rationalizations)
- 2 Good/Bad examples (workflow orchestration, scope validation)
- Integration with wolf-roles
- Verification checklist (6 items)
Scripts: orchestrate-workflow.mjs, validate-agent-changes.mjs, agent-executor.mjs
Supporting Skills (v1.0.0)
📚 wolf-instructions
Four-level instruction cascading (Global → Domain → Project → Role)
Use when:
- Resolving instruction conflicts
- Understanding priority hierarchy
- Loading contextual guidance
📝 wolf-adr
Architecture Decision Records system
Use when:
- Documenting architectural decisions
- Understanding past decisions
- Creating ADRs for major changes
Complete Skill Chain Diagram
SESSION START
|
v
[wolf-session-init] - MANDATORY ENTRY POINT
| Step 1: Query principles (BLOCKING)
| Step 2: Find archetype (BLOCKING)
| Step 3: Load governance (BLOCKING)
| Step 4: Load role (BLOCKING)
v
PRIMARY SKILL CHAIN (Sequential - DO NOT skip)
|
v
[wolf-principles] (v1.1.0)
| → Strategic guidance and decision framework
| → REQUIRED NEXT: wolf-archetypes
v
[wolf-archetypes] (v1.2.0)
| → Behavioral profile and evidence requirements
| → Apply lenses if needed (performance, security, accessibility, observability)
| → REQUIRED NEXT: wolf-governance
v
[wolf-governance] (v1.2.0)
| → Definition of Done, quality gates, compliance
| → REQUIRED NEXT: wolf-roles
| → REQUIRED ALWAYS: wolf-verification
v
[wolf-roles] (v1.2.0)
| → Role responsibilities, collaboration patterns
| → Use subagent templates for delegation
| → PRIMARY CHAIN COMPLETE ✅
v
IMPLEMENTATION BEGINS
|
v
[wolf-verification] (v1.1.0) - Called DURING work at checkpoints
| → Three-layer validation (CoVe, HSP, RAG)
| → Evidence collection
| → Confidence scoring
v
COMPLETION ✅
When to Use Each Skill - Decision Tree
START: Are you beginning new work or recovering context?
│
├─ YES → Use wolf-session-init (MANDATORY)
│ └─ Follow its 4-step blocking protocol
│
└─ NO: What do you need?
│
├─ "Strategic guidance / decision framework"
│ └─ Use wolf-principles
│ └─ MCP: mcp__wolf-knowledge__query_principles
│
├─ "What archetype for this work type?"
│ └─ Use wolf-archetypes
│ └─ MCP: mcp__wolf-knowledge__find_archetype
│ └─ OR Script: select-archetype.mjs
│
├─ "What are quality gates / Definition of Done?"
│ └─ Use wolf-governance
│ └─ MCP: mcp__wolf-knowledge__search_governance
│
├─ "What are my role responsibilities?"
│ └─ Use wolf-roles
│ └─ MCP: mcp__wolf-knowledge__get_role_guidance
│ └─ Use templates for subagent delegation
│
├─ "How do I validate evidence / check confidence?"
│ └─ Use wolf-verification
│ └─ MCP: mcp__wolf-core-ip__check_confidence
│
├─ "Need to automate archetype selection or evidence validation?"
│ └─ Use wolf-scripts-core
│ └─ Scripts: select-archetype.mjs, evidence-validator.mjs
│
├─ "Need to coordinate multiple agents?"
│ └─ Use wolf-scripts-agents
│ └─ Scripts: orchestrate-workflow.mjs, validate-agent-changes.mjs
│
├─ "Need to understand instruction priority?"
│ └─ Use wolf-instructions
│
└─ "Need to create ADR?"
└─ Use wolf-adr
Red Flags - STOP
If you catch yourself thinking:
- ❌ "I don't need the master skill, I know Wolf" - STOP. Master skill is updated with Phase 1 & 2 enhancements. Skills evolve. Read current version.
- ❌ "Master skills are just documentation" - NO. Master skill coordinates the entire framework. It shows skill chain and decision tree.
- ❌ "I can skip wolf-session-init and start coding" - FORBIDDEN. wolf-session-init is MANDATORY entry point with blocking gates.
- ❌ "I'll just use wolf-principles and skip the rest" - Wrong. Principles alone don't provide archetype, governance, or role context. Follow the chain.
- ❌ "The old workflow still works" - False. Phase 1 & 2 added blocking gates. Old workflow had 60-70% skip rates. New workflow enforces compliance.
STOP. Use the complete skill chain starting with wolf-session-init.
After Using This Skill
REQUIRED NEXT STEPS:
Master skill is a reference - not part of workflow chain
If starting new work: Use wolf-session-init as entry point
- Why: wolf-session-init is MANDATORY entry point with 4-step blocking protocol
- Gate: Cannot proceed to implementation without completing wolf-session-init
- This skill (wolf): Provides overview and decision tree, but wolf-session-init starts the actual workflow
If looking for specific guidance: Use decision tree above
- Navigate to appropriate skill based on need
- Follow MCP tool calls or script usage as documented
- Follow skill chains (each skill points to next required skill)
Return to this skill: When you need skill discovery or decision tree
- This is a reference/catalog skill
- Not part of mandatory workflow
- Use for navigation and overview
Common Workflows
Starting New Work (ALWAYS)
1. Use wolf-session-init (MANDATORY)
2. Follow blocking gates: principles → archetype → governance → role
3. Begin implementation with complete context
4. Use wolf-verification at checkpoints
Understanding a Specific Topic
1. Use decision tree above to find relevant skill
2. Read that skill for detailed guidance
3. Follow its "After Using This Skill" chain if applicable
Delegating to Subagent
1. Load wolf-roles for role guidance
2. Select appropriate role template (coder, pm, security, code-reviewer)
3. Fill placeholders with task details
4. Use Task tool to dispatch subagent with template
Integration Points
Wolf skills integrate with:
- GitHub: Labels trigger archetype selection, PR workflows enforce governance
- MCP Tools: All skills have corresponding MCP tool for querying Wolf knowledge
- Scripts: Automation scripts in wolf-scripts-core and wolf-scripts-agents
- Templates: Role templates in wolf-roles for subagent delegation
- ADRs: wolf-adr for documenting architectural decisions
- Journals: Required by governance for all work
Performance Benefits
Compared to MCP servers:
- 50x faster load times (<10ms vs 500ms)
- 40x fewer tokens (50 vs 2000)
- Zero memory overhead (on-demand vs 50MB process)
- Auto-composition based on context
- Enhanced with skill-chaining: Blocking gates enforce workflow compliance
Last Updated: 2025-11-14 Phase: Superpowers Skill-Chaining Enhancement v2.0.0 (Phase 3 in progress) Master Skill: Coordinates access to Wolf institutional knowledge