Refactor high-complexity React components in Dify frontend. Use when `pnpm analyze-component...
npx skills add synaptiai/agent-capability-standard --skill "gap-analysis-workflow"
Install specific skill from multi-skill repository
# Description
Identify capability gaps and propose new skills with prioritization. Use when analyzing missing capabilities, planning skill development, performing ontology expansion, or assessing coverage.
# SKILL.md
name: gap-analysis-workflow
description: Identify capability gaps and propose new skills with prioritization. Use when analyzing missing capabilities, planning skill development, performing ontology expansion, or assessing coverage.
argument-hint: "[goal] [scope] [constraints]"
disable-model-invocation: false
user-invocable: true
allowed-tools: Read, Grep, Bash, Edit, Git, Web
context: fork
agent: general-purpose
Intent
Run the composed workflow gap-analysis-workflow using atomic capability skills to systematically identify what capabilities are missing and prioritize their development.
Success criteria:
- Current capability coverage mapped with evidence
- Gaps identified with clear justification
- Relationships between existing and missing capabilities documented
- Prioritized roadmap for new skill development
- Audit trail of analysis process
Compatible schemas:
- docs/schemas/capability_ontology.yaml
- docs/schemas/workflow_catalog.yaml
Inputs
| Parameter | Required | Type | Description |
|---|---|---|---|
goal |
Yes | string | The analysis objective (e.g., "identify gaps for autonomous deployment") |
scope |
Yes | string|array | Domain, layer, or capability set to analyze |
constraints |
No | object | Limits (e.g., max new skills, priority criteria, timeline) |
reference_ontology |
No | string | Path to reference ontology for comparison |
existing_capabilities |
No | array | List of already-implemented capabilities |
Procedure
0) Create checkpoint marker if mutation might occur:
- Create .claude/checkpoint.ok after confirming rollback strategy
1) Invoke /inspect and store output as inspect_out
- Examine current capability landscape and documentation
2) Invoke /map-relationships and store output as map-relationships_out
- Map dependencies and connections between existing capabilities
3) Invoke /discover-relationship and store output as discover-relationship_out
- Identify implicit relationships and missing links
4) Invoke /compare-plans and store output as compare-plans_out
- Compare current state against ideal or reference ontology
5) Invoke /prioritize and store output as prioritize_out
- Rank gaps by impact, effort, and strategic value
6) Invoke /generate-plan and store output as generate-plan_out
- Create development roadmap for new capabilities
7) Invoke /audit and store output as audit_out
- Record analysis process and evidence
Output Contract
Return a structured object:
workflow_id: string # Unique analysis execution ID
goal: string # Analysis objective
status: completed | partial | failed
current_state:
capabilities_analyzed: integer
coverage_percentage: number # 0.0-1.0
layers_covered: array[string]
evidence_anchors: array[string]
gaps_identified:
total: integer
by_layer:
perception: array[string]
modeling: array[string]
reasoning: array[string]
action: array[string]
safety: array[string]
meta: array[string]
by_priority:
critical: array[string]
high: array[string]
medium: array[string]
low: array[string]
evidence_anchors: array[string]
relationships:
existing_dependencies: array[object]
missing_connections: array[object]
orphan_capabilities: array[string]
evidence_anchors: array[string]
comparison:
reference_ontology: string
alignment_score: number # 0.0-1.0
divergences: array[string]
evidence_anchors: array[string]
roadmap:
phases: array[object]
total_new_skills: integer
estimated_effort: string
dependencies: array[object]
evidence_anchors: array[string]
audit:
log_path: string
methodology: string
evidence_anchors: array[string]
confidence: number # 0.0-1.0
evidence_anchors: array[string]
assumptions: array[string]
Field Definitions
| Field | Type | Description |
|---|---|---|
workflow_id |
string | Unique identifier for this analysis |
current_state |
object | Summary of existing capability coverage |
gaps_identified |
object | Missing capabilities organized by layer and priority |
relationships |
object | Dependency mapping including missing connections |
comparison |
object | Alignment with reference ontology |
roadmap |
object | Phased development plan for new skills |
audit |
object | Analysis methodology and evidence trail |
confidence |
number | 0.0-1.0 based on evidence completeness |
evidence_anchors |
array | All evidence references collected |
assumptions |
array | Explicit assumptions made during analysis |
Examples
Example 1: Gap Analysis for Autonomous Code Review
Input:
goal: "Identify gaps for fully autonomous code review capability"
scope:
- "reasoning"
- "safety"
- "action"
constraints:
max_new_skills: 10
priority_criteria:
- "security_impact"
- "automation_potential"
reference_ontology: "schemas/capability_ontology.yaml"
Output:
workflow_id: "gap_20240115_120000_codereview"
goal: "Identify gaps for fully autonomous code review capability"
status: completed
current_state:
capabilities_analyzed: 45
coverage_percentage: 0.72
layers_covered:
- "reasoning"
- "safety"
- "action"
evidence_anchors:
- "file:schemas/capability_ontology.yaml"
- "file:skills/critique/SKILL.md"
gaps_identified:
total: 8
by_layer:
perception: []
modeling:
- "detect-code-smell"
- "identify-security-pattern"
reasoning:
- "compare-implementations"
- "evaluate-test-coverage"
action:
- "generate-review-comment"
- "apply-suggested-fix"
safety:
- "verify-no-regression"
- "constrain-auto-merge"
meta: []
by_priority:
critical:
- "verify-no-regression"
- "identify-security-pattern"
high:
- "detect-code-smell"
- "constrain-auto-merge"
medium:
- "compare-implementations"
- "generate-review-comment"
low:
- "evaluate-test-coverage"
- "apply-suggested-fix"
evidence_anchors:
- "file:schemas/capability_ontology.yaml:nodes"
- "tool:compare-plans:coverage_analysis"
relationships:
existing_dependencies:
- from: "critique"
to: "evaluate"
type: "requires"
- from: "plan"
to: "critique"
type: "soft_requires"
missing_connections:
- from: "detect-code-smell"
to: "critique"
type: "should_precede"
reason: "Code smells inform critique priorities"
- from: "verify-no-regression"
to: "act-plan"
type: "must_follow"
reason: "Regression check required after any code change"
orphan_capabilities: []
evidence_anchors:
- "tool:map-relationships:dependency_graph"
- "tool:discover-relationship:implicit_links"
comparison:
reference_ontology: "schemas/capability_ontology.yaml"
alignment_score: 0.72
divergences:
- "Missing specialized detection capabilities for code patterns"
- "No automated fix application in action layer"
- "Regression verification not formalized"
evidence_anchors:
- "tool:compare-plans:ontology_diff"
roadmap:
phases:
- phase: 1
name: "Security Foundation"
skills:
- "identify-security-pattern"
- "verify-no-regression"
rationale: "Critical for safe autonomous operation"
- phase: 2
name: "Detection Enhancement"
skills:
- "detect-code-smell"
- "constrain-auto-merge"
rationale: "Improves review quality and safety"
- phase: 3
name: "Automation Expansion"
skills:
- "compare-implementations"
- "generate-review-comment"
- "evaluate-test-coverage"
- "apply-suggested-fix"
rationale: "Full autonomous review capability"
total_new_skills: 8
estimated_effort: "2-3 sprints"
dependencies:
- skill: "apply-suggested-fix"
requires: ["verify-no-regression", "constrain-auto-merge"]
evidence_anchors:
- "tool:prioritize:impact_matrix"
- "tool:generate-plan:roadmap"
audit:
log_path: ".claude/audit/gap_20240115_120000_codereview.log"
methodology: "Systematic comparison against reference ontology with layer-by-layer analysis"
evidence_anchors:
- "file:.claude/audit/gap_20240115_120000_codereview.log"
confidence: 0.85
evidence_anchors:
- "file:schemas/capability_ontology.yaml"
- "tool:map-relationships:dependency_graph"
- "tool:compare-plans:ontology_diff"
- "tool:prioritize:impact_matrix"
assumptions:
- "Reference ontology is current and complete"
- "Existing skills are correctly implemented"
- "Priority criteria reflect actual business needs"
Evidence pattern: Ontology comparison, dependency graph analysis, impact-based prioritization.
Verification
- [ ] Coverage Analyzed: All capabilities in scope examined
- [ ] Gaps Documented: Each gap has layer classification and priority
- [ ] Relationships Mapped: Dependencies and missing connections identified
- [ ] Comparison Complete: Alignment score computed against reference
- [ ] Roadmap Generated: Phased plan with dependencies
- [ ] Audit Trail: Analysis methodology documented
Verification tools: Read (for ontology files), Grep (for capability search), Bash (for validation)
Safety Constraints
mutation: falserequires_checkpoint: falserequires_approval: falserisk: low
Capability-specific rules:
- Do not create new skills during analysis (discovery only)
- Validate all capability references against ontology
- Document assumptions about missing capabilities
- Flag potential security implications of gaps
- Preserve existing ontology structure
Composition Patterns
Commonly follows:
- inspect - After initial codebase exploration
- retrieve - After fetching reference documentation
Commonly precedes:
- generate-plan - To create detailed skill specifications
- prioritize - To refine gap prioritization
- summarize - To create executive summary
Anti-patterns:
- Never skip relationship mapping before prioritization
- Never propose skills without checking ontology for existing alternatives
- Never prioritize without defined criteria
- Never generate roadmap without dependency analysis
Workflow references:
- See workflow_catalog.yaml#gap-analysis-workflow for step definitions
- See capability_ontology.yaml for reference structure
# Supported AI Coding Agents
This skill is compatible with the SKILL.md standard and works with all major AI coding agents:
Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.