Get the FREE Ultimate OpenClaw Setup Guide →

gap-analysis-workflow

npx machina-cli add skill synaptiai/agent-capability-standard/capability-gap-analysis --openclaw
Files (1)
SKILL.md
10.3 KB

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:

  • reference/capability_ontology.yaml
  • reference/workflow_catalog.yaml

Inputs

ParameterRequiredTypeDescription
goalYesstringThe analysis objective (e.g., "identify gaps for autonomous deployment")
scopeYesstring|arrayDomain, layer, or capability set to analyze
constraintsNoobjectLimits (e.g., max new skills, priority criteria, timeline)
reference_ontologyNostringPath to reference ontology for comparison
existing_capabilitiesNoarrayList of already-implemented capabilities

Procedure

  1. Create checkpoint marker if mutation might occur:

    • Create .claude/checkpoint.ok after confirming rollback strategy
  2. Invoke /inspect and store output as inspect_out

    • Examine current capability landscape and documentation
  3. Invoke /map-relationships and store output as map-relationships_out

    • Map dependencies and connections between existing capabilities
  4. Invoke /discover-relationship and store output as discover-relationship_out

    • Identify implicit relationships and missing links
  5. Invoke /compare-plans and store output as compare-plans_out

    • Compare current state against ideal or reference ontology
  6. Invoke /prioritize and store output as prioritize_out

    • Rank gaps by impact, effort, and strategic value
  7. Invoke /generate-plan and store output as generate-plan_out

    • Create development roadmap for new capabilities
  8. 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

FieldTypeDescription
workflow_idstringUnique identifier for this analysis
current_stateobjectSummary of existing capability coverage
gaps_identifiedobjectMissing capabilities organized by layer and priority
relationshipsobjectDependency mapping including missing connections
comparisonobjectAlignment with reference ontology
roadmapobjectPhased development plan for new skills
auditobjectAnalysis methodology and evidence trail
confidencenumber0.0-1.0 based on evidence completeness
evidence_anchorsarrayAll evidence references collected
assumptionsarrayExplicit 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: false
  • requires_checkpoint: false
  • requires_approval: false
  • risk: 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 reference/workflow_catalog.yaml#gap-analysis-workflow for step definitions
  • See reference/capability_ontology.yaml for reference structure

Source

git clone https://github.com/synaptiai/agent-capability-standard/blob/main/skills/capability-gap-analysis/SKILL.mdView on GitHub

Overview

gap-analysis-workflow orchestrates a sequence of atomic capability skills to identify missing capabilities and prioritize development. It maps current capability coverage, identifies gaps with justification, documents relationships to existing capabilities, and generates a prioritized development roadmap with an auditable trail of the analysis.

How This Skill Works

The workflow runs as a multi-step process: inspect the current capability landscape, map relationships between capabilities, discover implicit links, compare the current state to a reference ontology, prioritize gaps, generate a development plan, and audit the entire process. Each step stores its output to form an evidence-backed, traceable gap-analysis report.

When to Use It

  • When analyzing missing capabilities and how they affect overall coverage.
  • When planning skill development and a structured onboarding or upgrade roadmap.
  • During ontology expansion to align with reference schemas and standards.
  • When assessing coverage against a reference ontology or workflow catalog.
  • When creating an auditable governance trail for capability analysis and decision making.

Quick Start

  1. Step 1: Define goal, scope, and constraints for the analysis.
  2. Step 2: Run the workflow: inspect -> map-relationships -> discover-relationship -> compare-plans -> prioritize -> generate-plan -> audit.
  3. Step 3: Review gaps, validate against reference ontology, and publish the prioritized roadmap with evidence anchors.

Best Practices

  • Define goal, scope, and constraints up front to guide the analysis.
  • Ground analysis with reference_ontology and existing_capabilities for baseline context.
  • Capture outputs from each step (inspect, map-relationships, etc.) as evidence anchors.
  • Provide clear justification for each gap and map it to dependencies.
  • Maintain an audit trail with checkpoint markers and versioned outputs.

Example Use Cases

  • A robotics platform uses gap-analysis-workflow to identify missing perception and planning capabilities and prioritizes safety-related skills.
  • An autonomous vehicle team expands its ontology to include new decision-making capabilities based on detected gaps.
  • A SaaS product analyzes integration capabilities and generates a prioritized roadmap for API and middleware skills.
  • A research group aligns capabilities to a reference ontology to standardize evaluation criteria.
  • An enterprise AI assistant documents gaps against a workflow catalog and creates a governance-friendly audit trail.

Frequently Asked Questions

Add this skill to your agents
Sponsor this space

Reach thousands of developers