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ac-complexity-assessor

Assess feature and project complexity. Use when estimating effort, determining spec pipeline type, calculating cost estimates, or planning resource allocation.

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The canonical home for this skill is ac-complexity-assessor in fernandezbaptiste/Skrillz

SKILL.md
Quality
Evals
Security

AC Complexity Assessor

Assess complexity for effort estimation and planning.

Purpose

Analyzes features and projects to determine complexity levels, estimate effort, and select appropriate processing pipelines.

Quick Start

from scripts.complexity_assessor import ComplexityAssessor

assessor = ComplexityAssessor(project_dir)
assessment = await assessor.assess_project()
print(assessment.pipeline_type)  # SIMPLE/STANDARD/COMPLEX
print(assessment.estimated_hours)

Assessment Output

{
  "project_complexity": "STANDARD",
  "pipeline_type": "STANDARD",
  "metrics": {
    "total_features": 75,
    "dependency_depth": 4,
    "category_count": 8,
    "integration_points": 5,
    "technology_complexity": 3
  },
  "estimates": {
    "total_hours": 120,
    "estimated_cost_usd": 45.00,
    "estimated_sessions": 15,
    "features_per_session": 5
  },
  "feature_estimates": [
    {
      "id": "auth-001",
      "complexity": "low",
      "estimated_hours": 1.5,
      "factors": ["standard_pattern", "no_dependencies"]
    }
  ],
  "recommendations": [
    "Consider parallelizing UI features",
    "auth-003 may need more time due to OAuth"
  ]
}

Complexity Levels

SIMPLE (1-3 phases)

  • < 20 features
  • Shallow dependencies (depth < 2)
  • Single technology
  • No external integrations

STANDARD (7 phases)

  • 20-100 features
  • Moderate dependencies (depth 2-5)
  • 2-3 technologies
  • Limited integrations

COMPLEX (8+ phases)

  • 100 features

  • Deep dependencies (depth > 5)
  • Multiple technologies
  • Many integrations

Complexity Factors

Feature Complexity

  • Implementation difficulty
  • Test complexity
  • Documentation needs
  • Integration requirements

Project Complexity

  • Total feature count
  • Dependency graph depth
  • Technology stack breadth
  • External integrations

Risk Factors

  • Unfamiliar technologies
  • Complex algorithms
  • Security requirements
  • Performance constraints

Pipeline Selection

SIMPLE Pipeline:
  1. Plan → 2. Implement → 3. Verify

STANDARD Pipeline:
  1. Analyze → 2. Plan → 3. Test Design
  4. Implement → 5. Test → 6. Review → 7. Verify

COMPLEX Pipeline:
  1. Deep Analyze → 2. Architecture → 3. Plan
  4. Test Design → 5. Implement → 6. Test
  7. Integration → 8. Review → 9. Verify

Cost Estimation

cost = (features * avg_tokens_per_feature * cost_per_token)
     + (sessions * session_overhead)
     + (complexity_multiplier * base_cost)

API Reference

See scripts/complexity_assessor.py for full implementation.

Repository
fernandezbaptiste/Skrillz
Path

.claude/skills/ac-complexity-assessor/SKILL.md

Commit

93ed392

Last updated
First committed

Canonical home

fernandezbaptiste/Skrillz
In sync

since Sep 12, 2026

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