Agent skill
when-analyzing-skill-gaps-use-skill-gap-analyzer
Install this agent skill to your Project
npx add-skill https://github.com/DNYoussef/context-cascade/tree/main/skills/foundry/when-analyzing-skill-gaps-use-skill-gap-analyzer
SKILL.md
/============================================================================/ /* WHEN-ANALYZING-SKILL-GAPS-USE-SKILL-GAP-ANALYZER SKILL :: VERILINGUA x VERIX EDITION / /============================================================================*/
name: when-analyzing-skill-gaps-use-skill-gap-analyzer version: 1.0.0 description: | [assert|neutral] Analyze skill library to identify coverage gaps, redundant overlaps, optimization opportunities, and provide recommendations for skill portfolio improvement [ground:given] [conf:0.95] [state:confirmed] category: foundry tags:
- meta-tool
- skill-management
- gap-analysis
- portfolio-optimization author: ruv cognitive_frame: primary: compositional goal_analysis: first_order: "Execute when-analyzing-skill-gaps-use-skill-gap-analyzer workflow" second_order: "Ensure quality and consistency" third_order: "Enable systematic foundry processes"
/----------------------------------------------------------------------------/ /* S0 META-IDENTITY / /----------------------------------------------------------------------------*/
[define|neutral] SKILL := { name: "when-analyzing-skill-gaps-use-skill-gap-analyzer", category: "foundry", version: "1.0.0", layer: L1 } [ground:given] [conf:1.0] [state:confirmed]
/----------------------------------------------------------------------------/ /* S1 COGNITIVE FRAME / /----------------------------------------------------------------------------*/
[define|neutral] COGNITIVE_FRAME := { frame: "Compositional", source: "German", force: "Build from primitives?" } [ground:cognitive-science] [conf:0.92] [state:confirmed]
Kanitsal Cerceve (Evidential Frame Activation)
Kaynak dogrulama modu etkin.
/----------------------------------------------------------------------------/ /* S2 TRIGGER CONDITIONS / /----------------------------------------------------------------------------*/
[define|neutral] TRIGGER_POSITIVE := { keywords: ["when-analyzing-skill-gaps-use-skill-gap-analyzer", "foundry", "workflow"], context: "user needs when-analyzing-skill-gaps-use-skill-gap-analyzer capability" } [ground:given] [conf:1.0] [state:confirmed]
/----------------------------------------------------------------------------/ /* S3 CORE CONTENT / /----------------------------------------------------------------------------*/
Skill Execution Criteria
When to Use This Skill
- [AUTO-EXTRACTED from skill description and content]
- [Task patterns this skill is optimized for]
- [Workflow contexts where this skill excels]
When NOT to Use This Skill
- [Situations where alternative skills are better suited]
- [Anti-patterns that indicate wrong skill choice]
- [Edge cases this skill doesn't handle well]
Success Criteria
- primary_outcome: "[SKILL-SPECIFIC measurable result based on skill purpose]"
- [assert|neutral] quality_threshold: 0.85 [ground:acceptance-criteria] [conf:0.90] [state:provisional]
- verification_method: "[How to validate skill executed correctly and produced expected outcome]"
Edge Cases
- case: "Ambiguous or incomplete input" handling: "Request clarification, document assumptions, proceed with explicit constraints"
- case: "Conflicting requirements or constraints" handling: "Surface conflict to user, propose resolution options, document trade-offs"
- case: "Insufficient context for quality execution" handling: "Flag missing information, provide template for needed context, proceed with documented limitations"
Skill Guardrails
NEVER:
- "[SKILL-SPECIFIC anti-pattern that breaks methodology]"
- "[Common mistake that degrades output quality]"
- "[Shortcut that compromises skill effectiveness]" ALWAYS:
- "[SKILL-SPECIFIC requirement for successful execution]"
- "[Critical step that must not be skipped]"
- "[Quality check that ensures reliable output]"
Evidence-Based Execution
self_consistency: "After completing this skill, verify output quality by [SKILL-SPECIFIC validation approach]" program_of_thought: "Decompose this skill execution into: [SKILL-SPECIFIC sequential steps]" plan_and_solve: "Plan: [SKILL-SPECIFIC planning phase] -> Execute: [SKILL-SPECIFIC execution phase] -> Verify: [SKILL-SPECIFIC verification phase]"
Skill Gap Analyzer
Kanitsal Cerceve (Evidential Frame Activation)
Kaynak dogrulama modu etkin.
Purpose: Perform comprehensive analysis of skill library to identify missing capabilities, redundant functionality, optimization opportunities, and provide actionable recommendations for skill portfolio improvement.
When to Use This Skill
- When building a new skill library
- Quarterly skill portfolio reviews
- Before large refactoring efforts
- When considering new skill additions
- After major project pivots
- When optimizing resource allocation
Analysis Dimensions
1. Coverage Gap Analysis
- Domain coverage mapping
- Missing capability identification
- Use case scenario testing
- Workflow completeness assessment
- Integration point analysis
2. Redundancy Detection
- Duplicate functionality identification
- Overlapping capability mapping
- Consolidation opportunity analysis
- Version conflict detection
- Naming collision identification
3. Optimization Opportunities
- Under-utilized skill detection
- Over-complex skill identification
- Composability improvement suggestions
- Dependency optimization
- Performance bottleneck analysis
4. Usage Pattern Analysis
- Frequency metrics
- Co-occurrence patterns
- Success rate tracking
- Token efficiency measurement
- Agent utilization patterns
5. Recommendation Generation
- Prioritized action items
- Consolidation strategies
- New skill proposals
- Deprecation candidates
- Restructuring plans
Execution Process
Phase 1: Library Inventory
# Initialize analysis session
npx claude-flow@alpha hooks pre-task --description "Analyzing skill library gaps"
# Scan skill directories
find ~/.claude/skills -name "SKILL.md" -o -name "*.skill.md"
Inventory Script:
function inventorySkills(skillDirectory) {
const inventory = {
totalSkills: 0,
categories: {},
capabilities: {},
agents: {},
complexity: {},
tags: {}
};
// Parse each SKILL.md file
const skillFiles = findSki
/*----------------------------------------------------------------------------*/
/* S4 SUCCESS CRITERIA */
/*----------------------------------------------------------------------------*/
[define|neutral] SUCCESS_CRITERIA := {
primary: "Skill execution completes successfully",
quality: "Output meets quality thresholds",
verification: "Results validated against requirements"
} [ground:given] [conf:1.0] [state:confirmed]
/*----------------------------------------------------------------------------*/
/* S5 MCP INTEGRATION */
/*----------------------------------------------------------------------------*/
[define|neutral] MCP_INTEGRATION := {
memory_mcp: "Store execution results and patterns",
tools: ["mcp__memory-mcp__memory_store", "mcp__memory-mcp__vector_search"]
} [ground:witnessed:mcp-config] [conf:0.95] [state:confirmed]
/*----------------------------------------------------------------------------*/
/* S6 MEMORY NAMESPACE */
/*----------------------------------------------------------------------------*/
[define|neutral] MEMORY_NAMESPACE := {
pattern: "skills/foundry/when-analyzing-skill-gaps-use-skill-gap-analyzer/{project}/{timestamp}",
store: ["executions", "decisions", "patterns"],
retrieve: ["similar_tasks", "proven_patterns"]
} [ground:system-policy] [conf:1.0] [state:confirmed]
[define|neutral] MEMORY_TAGGING := {
WHO: "when-analyzing-skill-gaps-use-skill-gap-analyzer-{session_id}",
WHEN: "ISO8601_timestamp",
PROJECT: "{project_name}",
WHY: "skill-execution"
} [ground:system-policy] [conf:1.0] [state:confirmed]
/*----------------------------------------------------------------------------*/
/* S7 SKILL COMPLETION VERIFICATION */
/*----------------------------------------------------------------------------*/
[direct|emphatic] COMPLETION_CHECKLIST := {
agent_spawning: "Spawn agents via Task()",
registry_validation: "Use registry agents only",
todowrite_called: "Track progress with TodoWrite",
work_delegation: "Delegate to specialized agents"
} [ground:system-policy] [conf:1.0] [state:confirmed]
/*----------------------------------------------------------------------------*/
/* S8 ABSOLUTE RULES */
/*----------------------------------------------------------------------------*/
[direct|emphatic] RULE_NO_UNICODE := forall(output): NOT(unicode_outside_ascii) [ground:windows-compatibility] [conf:1.0] [state:confirmed]
[direct|emphatic] RULE_EVIDENCE := forall(claim): has(ground) AND has(confidence) [ground:verix-spec] [conf:1.0] [state:confirmed]
[direct|emphatic] RULE_REGISTRY := forall(agent): agent IN AGENT_REGISTRY [ground:system-policy] [conf:1.0] [state:confirmed]
/*----------------------------------------------------------------------------*/
/* PROMISE */
/*----------------------------------------------------------------------------*/
[commit|confident] <promise>WHEN_ANALYZING_SKILL_GAPS_USE_SKILL_GAP_ANALYZER_VERILINGUA_VERIX_COMPLIANT</promise> [ground:self-validation] [conf:0.99] [state:confirmed]
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