Agent skill

when-analyzing-skill-gaps-use-skill-gap-analyzer

Stars 27
Forks 6

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

bash
# 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:

javascript
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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