name	wolf
description	Master skill for Wolf Agents institutional knowledge and behavioral patterns (v1.1.0 with skill-chaining)
version	1.1.0
triggers	wolf, agent, archetype, principles, governance, behavioral profile, wolf framework

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

wolf

Install Skill

SKILL.md

Wolf Agents Master Skill

What's New in v1.1.0

Available Wolf Skills

Core Framework Skills (v1.1.0 - v1.2.0)

🚀 wolf-session-init (v1.0.0) START HERE

🎯 wolf-principles (v1.1.0)

🔄 wolf-archetypes (v1.2.0)

🛡️ wolf-governance (v1.2.0)

📋 wolf-roles (v1.2.0)

✅ wolf-verification (v1.1.0)

Automation & Scripts (v1.1.0)

⚙️ wolf-scripts-core (v1.1.0)

🤖 wolf-scripts-agents (v1.1.0)

Supporting Skills (v1.0.0)

📚 wolf-instructions

📝 wolf-adr

Complete Skill Chain Diagram

When to Use Each Skill - Decision Tree

Red Flags - STOP

After Using This Skill

Common Workflows

Starting New Work (ALWAYS)

Understanding a Specific Topic

Delegating to Subagent

Integration Points

Performance Benefits