Staged Content Refinement

Process extracted skills and docs from multiple projects into consolidated, project-agnostic patterns.

Installation

OpenClaw / Moltbot / Clawbot

npx clawhub@latest install refinement

Before Starting

1. •

   Verify staging has content from multiple projects:

   • •ai/staging/skills/ — Extracted skills
   • •ai/staging/docs/ — Extracted methodology docs
2. •

   Load quality criteria: ../extraction/references/skill-quality-criteria.md

Refinement Process

Phase 1: Inventory

Scan all staged content and catalog what exists.

For skills:

ai/staging/skills/
├── [project-a]-[category]/
├── [project-b]-[category]/
└── ...

For docs:

ai/staging/docs/
├── [project-a]-summary.md
├── [project-a]-design-system.md
├── [project-b]-summary.md
└── ...

Create inventory:

Phase 2: Pattern Analysis

Identify patterns that appear across multiple projects.

Look for:

1. •

   Design system patterns (highest priority)

   • •Common token structures
   • •Similar aesthetic approaches
   • •Shared color/typography patterns
2. •

   Architecture patterns

   • •Similar folder structures
   • •Common component organization
   • •Shared data flow patterns
3. •

   Workflow patterns

   • •Common Makefile targets
   • •Similar CI/CD approaches
   • •Shared dev setup patterns
4. •

   Methodology insights

   • •Decision-making patterns
   • •Trade-offs that appear repeatedly
   • •Common anti-patterns discovered

Questions to answer:

• •What patterns appear in 2+ projects?
• •What's project-specific vs generalizable?
• •What methodology insights can update the main docs?

Phase 2.5: Conflict Detection

Before consolidating, check for conflicts with existing skills.

Scan existing skills:

ls ai/skills/*/

For each staged skill, check:

Conflict resolution:

Run overlap check:

/check-overlaps

Document conflicts:

• •Note which existing skills overlap
• •Decide: merge into existing vs create new
• •Update existing skills if merging

Phase 3: Consolidation

Merge similar patterns into unified, project-agnostic skills.

For each pattern group:

1. •Identify the core — What's common across all instances?
2. •Strip project specifics — Remove project names, specific values
3. •Generalize — Make it applicable to any project
4. •Enhance — Add insights learned from seeing multiple implementations

Example consolidation:

Staged:
├── project-a-design-system/  (retro-futuristic tokens)
├── project-b-design-system/  (video game UI tokens)
└── project-c-design-system/  (minimal dark tokens)

Consolidated:
└── design-system-patterns/   (how to build distinctive design systems)
    - Token structure patterns
    - Aesthetic direction documentation
    - Common anti-patterns across projects

Consolidation rules:

Phase 4: Methodology Updates

Extract insights to update the main methodology docs.

Review staged docs for:

1. •New patterns not in current methodology
2. •Refinements to existing approaches
3. •Anti-patterns discovered across projects
4. •Decision rationale worth capturing

Update locations:

Phase 5: Promotion

Move refined skills to active locations.

Skill promotion:

# From staging to active
mv ai/staging/skills/[refined-skill]/ ai/skills/[refined-skill]/

Doc updates:

• •Update main docs with methodology insights
• •Archive or delete processed staging content

Post-promotion:

• •Verify skills have proper descriptions
• •Test skill activation with sample prompts
• •Clean up staging folder

Phase 6: Testing

After promotion, verify skills work correctly.

Activation testing: For each promoted skill, test that it activates on expected triggers:

Test: "I need to [trigger from When to Use]"
Expected: Skill should be suggested/activated

Quality verification:

• • Description triggers correctly
• • Code examples are valid and runnable
• • NEVER Do section is actionable
• • Related skills are linked correctly

Rollback if issues:

# If skill has problems, move back to staging
mv ai/skills/[category]/[skill]/ ai/staging/skills/

Document test results:

• •Note any activation issues
• •Record false positives (activates when shouldn't)
• •Record false negatives (doesn't activate when should)

Error Handling

Output Locations

Refined skills go to:

ai/skills/           # Cursor-specific skills
ai/skills/           # Claude Code skills (if applicable)

Methodology updates go to:

docs/
├── METHODOLOGY.md        # Philosophy and approach
├── TECH-STACK.md         # Technology patterns
├── ARCHITECTURE.md       # Skill/agent architecture
└── WORKFLOW.md           # Processes

Staging cleanup:

ai/staging/skills/        # Clear after processing
ai/staging/docs/          # Clear after processing
ai/archive/               # (optional) Keep for reference

Consolidation Examples

Design Systems

Before (3 project-specific skills):

• •project-a-design-system — Retro-futuristic tokens
• •project-b-design-system — Video game UI tokens
• •project-c-design-system — Cyberpunk terminal tokens

After (1 consolidated skill):

• •distinctive-design-systems — How to create design systems with personality
  • •Token structure patterns
  • •Aesthetic documentation approach
  • •Anti-patterns (generic bootstrap, "clean" without personality)
  • •Examples from different aesthetic directions

Architecture

Before (multiple docs):

• •project-a-architecture.md
• •project-b-architecture.md

After:

• •Update docs/ARCHITECTURE.md with common patterns
• •Create skill only if patterns are unique enough

NEVER Do

• •NEVER keep project-specific details in consolidated skills
• •NEVER create redundant skills — Merge similar patterns
• •NEVER skip methodology updates — Insights should flow back to docs
• •NEVER promote low-quality skills — Must pass quality criteria
• •NEVER leave staging cluttered — Clean up after processing

Quality Check

Before finishing refinement:

• • All staged content reviewed?
• • Conflict detection completed (Phase 2.5)?
• • Common patterns identified and consolidated?
• • Consolidated skills are project-agnostic?
• • Methodology docs updated with insights?
• • Refined skills promoted to active locations?
• • Activation testing completed (Phase 6)?
• • Staging folder cleaned up?

Related Skills

• •Agent: ai/agents/refinement/ — Autonomous refinement workflow
• •Command: /refine-staged — Quick refinement command
• •Command: /promote-skill — Single skill promotion
• •Previous step: ai/skills/extraction/ — Pattern extraction
• •Quality criteria: ../extraction/references/skill-quality-criteria.md