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autonomous-development

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โญ 14๐Ÿด 11๐Ÿ“… Jan 19, 2026

SKILL.md


name: autonomous-development description: Comprehensive autonomous development strategies including milestone planning, incremental implementation, auto-debugging, and continuous quality assurance for full development lifecycle management version: 1.0.0

Overview

The Autonomous Development skill provides comprehensive strategies, patterns, and best practices for managing full development lifecycles autonomously - from user requirements to production-ready implementation with minimal human intervention.

When to Apply

Use Autonomous Development strategies when:

  • Implementing features from high-level requirements
  • Managing complex multi-phase development projects
  • Need to maintain quality while developing autonomously
  • Implementing with continuous testing and validation
  • Debugging and fixing issues automatically
  • Ensuring parameter consistency and type safety

Milestone Planning Strategies

Requirements Decomposition

Pattern: Feature-to-Milestone Mapping

User Requirement โ†’ Feature Breakdown โ†’ Milestone Plan

Example: "Add MQTT broker with certificate support"

Decomposition:
1. Dependencies & Configuration (Simple)
   - Install required libraries
   - Create configuration module
   - Time: 10-15 minutes

2. Core Functionality (Medium)
   - Implement main feature logic
   - Add error handling
   - Time: 20-30 minutes

3. Integration & Testing (Medium)
   - Write unit tests
   - Write integration tests
   - Time: 15-25 minutes

4. Documentation (Simple)
   - API documentation
   - Usage examples
   - Time: 10-15 minutes

Complexity Assessment Matrix

Simple Milestone:
โ”œโ”€ Single file modification
โ”œโ”€ Well-defined scope
โ”œโ”€ No external dependencies
โ”œโ”€ Existing patterns to follow
โ””โ”€ Estimated: 10-20 minutes

Medium Milestone:
โ”œโ”€ Multiple file modifications
โ”œโ”€ Some external dependencies
โ”œโ”€ Integration with existing code
โ”œโ”€ Moderate complexity
โ””โ”€ Estimated: 20-45 minutes

Complex Milestone:
โ”œโ”€ Multiple component changes
โ”œโ”€ New dependencies or frameworks
โ”œโ”€ Significant integration work
โ”œโ”€ Architectural considerations
โ””โ”€ Estimated: 45-90 minutes

Expert Milestone:
โ”œโ”€ Major architectural changes
โ”œโ”€ Multiple system integrations
โ”œโ”€ Advanced algorithms or patterns
โ”œโ”€ Security-critical implementations
โ””โ”€ Estimated: 90+ minutes

Milestone Sequencing

Pattern: Dependency-First Ordering

Order milestones to minimize dependencies:

1. Foundation Layer
   - Dependencies
   - Configuration
   - Data models

2. Core Logic Layer
   - Business logic
   - Core algorithms
   - Main functionality

3. Integration Layer
   - API endpoints
   - External integrations
   - Service connections

4. Quality Layer
   - Testing
   - Documentation
   - Validation

Incremental Development Patterns

Commit-Per-Milestone Strategy

Pattern: Working State Commits

Each milestone must result in a working state:

โœ… Good Milestone:
- Feature partially complete but functional
- All tests pass for implemented functionality
- No breaking changes to existing code
- Commit: "feat: add user authentication (phase 1/3)"

โŒ Bad Milestone:
- Feature incomplete and non-functional
- Tests failing
- Breaking changes uncommitted
- Half-implemented logic

Conventional Commit Format

<type>(<scope>): <description>

[optional body]

[optional footer]

Types:
- feat: New feature
- fix: Bug fix
- refactor: Code refactoring
- test: Adding tests
- docs: Documentation
- chore: Maintenance
- perf: Performance improvement

Examples:
feat(mqtt): add broker connection with SSL
fix(auth): correct token validation logic
test(api): add integration tests for user endpoints
docs(readme): update installation instructions

Progressive Enhancement Pattern

Start simple, enhance progressively:

Phase 1: Basic Implementation
โ”œโ”€ Core functionality only
โ”œโ”€ No error handling
โ”œโ”€ No optimization
โ””โ”€ Purpose: Prove concept works

Phase 2: Error Handling
โ”œโ”€ Add try-catch blocks
โ”œโ”€ Add input validation
โ”œโ”€ Add logging
โ””โ”€ Purpose: Make it robust

Phase 3: Optimization
โ”œโ”€ Performance improvements
โ”œโ”€ Memory optimization
โ”œโ”€ Caching if needed
โ””โ”€ Purpose: Make it efficient

Phase 4: Polish
โ”œโ”€ Documentation
โ”œโ”€ Examples
โ”œโ”€ Edge case handling
โ””โ”€ Purpose: Make it production-ready

Auto-Debugging Strategies

Error Classification System

Error Categories and Fix Strategies:

1. Syntax Errors (100% auto-fixable)
   - Missing colons, brackets, quotes
   - Indentation errors
   - Strategy: Parse and fix immediately

2. Import Errors (95% auto-fixable)
   - Missing imports
   - Incorrect module paths
   - Strategy: Auto-add imports, fix paths

3. Type Errors (90% auto-fixable)
   - Type mismatches
   - Type hint violations
   - Strategy: Add type conversions or fix hints

4. Name Errors (85% auto-fixable)
   - Undefined variables
   - Typos in names
   - Strategy: Fix typos or add definitions

5. Logic Errors (60% auto-fixable)
   - Wrong algorithm
   - Incorrect conditions
   - Strategy: Analyze and refactor logic

6. Integration Errors (70% auto-fixable)
   - Connection failures
   - API mismatches
   - Strategy: Add retry logic, fix endpoints

7. Performance Errors (40% auto-fixable)
   - Timeouts
   - Memory issues
   - Strategy: Optimize algorithms, add caching

Debug Loop Pattern

Maximum 5 iterations per issue:

Iteration 1: Quick Fix (confidence > 90%)
โ”œโ”€ Fix obvious issues (typos, imports)
โ”œโ”€ Success rate: 70%
โ””โ”€ Time: 30 seconds

Iteration 2: Pattern-Based Fix (confidence 70-90%)
โ”œโ”€ Apply known successful patterns
โ”œโ”€ Success rate: 50%
โ””โ”€ Time: 1-2 minutes

Iteration 3: Analysis-Based Fix (confidence 50-70%)
โ”œโ”€ Deep error analysis
โ”œโ”€ Root cause investigation
โ”œโ”€ Success rate: 30%
โ””โ”€ Time: 3-5 minutes

Iteration 4: Alternative Approach (confidence 30-50%)
โ”œโ”€ Try different implementation
โ”œโ”€ Success rate: 20%
โ””โ”€ Time: 5-10 minutes

Iteration 5: Last Attempt (confidence < 30%)
โ”œโ”€ Aggressive fixes
โ”œโ”€ Success rate: 10%
โ””โ”€ Time: 10-15 minutes

If all iterations fail โ†’ Manual intervention required

Common Fix Patterns

Connection Retry Pattern

# Problem: Connection refused
# Fix: Add exponential backoff retry

import time
from functools import wraps

def with_retry(max_attempts=3, backoff_factor=2):
    def decorator(func):
        @wraps(func)
        def wrapper(*args, **kwargs):
            for attempt in range(max_attempts):
                try:
                    return func(*args, **kwargs)
                except ConnectionError as e:
                    if attempt == max_attempts - 1:
                        raise
                    delay = backoff_factor ** attempt
                    time.sleep(delay)
            return None
        return wrapper
    return decorator

@with_retry(max_attempts=3)
def connect_to_service():
    # Connection logic
    pass

Type Conversion Pattern

# Problem: Type mismatch (str vs int)
# Fix: Add safe type conversion

def safe_int(value, default=0):
    try:
        return int(value)
    except (ValueError, TypeError):
        return default

# Usage
user_id = safe_int(request.params.get('user_id'))

Null Safety Pattern

# Problem: NoneType attribute error
# Fix: Add null checks

# Bad
result = data.get('user').get('name')

# Good
result = data.get('user', {}).get('name', 'Unknown')

# Better
user = data.get('user')
result = user.get('name', 'Unknown') if user else 'Unknown'

Parameter Validation Pattern

# Problem: Invalid parameters
# Fix: Add validation decorator

from functools import wraps
from typing import get_type_hints

def validate_params(func):
    @wraps(func)
    def wrapper(*args, **kwargs):
        hints = get_type_hints(func)
        for param_name, param_type in hints.items():
            if param_name in kwargs:
                value = kwargs[param_name]
                if not isinstance(value, param_type):
                    raise TypeError(
                        f"{param_name} must be {param_type}, "
                        f"got {type(value)}"
                    )
        return func(*args, **kwargs)
    return wrapper

@validate_params
def create_user(name: str, age: int) -> dict:
    return {'name': name, 'age': age}

Parameter Consistency Validation

Cross-File Parameter Validation

Critical validation checklist:

1. Function Signatures
   โœ“ Parameter names match between definition and calls
   โœ“ Parameter order consistent
   โœ“ Default values aligned

2. Configuration Files
   โœ“ Config keys match code usage
   โœ“ Environment variables consistent
   โœ“ No undefined config references

3. Type Consistency
   โœ“ Type hints present and correct
   โœ“ Return types specified
   โœ“ Type conversions explicit

4. API Contracts
   โœ“ Request parameters match backend expectations
   โœ“ Response structure consistent
   โœ“ Error codes standardized

5. Database Schemas
   โœ“ Column names match model attributes
   โœ“ Data types aligned
   โœ“ Foreign key constraints correct

Validation Automation Pattern

# Automated parameter validation

def validate_function_calls(codebase):
    issues = []

    # Extract all function definitions
    definitions = extract_function_definitions(codebase)

    # Extract all function calls
    calls = extract_function_calls(codebase)

    for call in calls:
        definition = definitions.get(call.function_name)

        if not definition:
            issues.append({
                'type': 'undefined_function',
                'function': call.function_name,
                'location': call.location
            })
            continue

        # Check parameter count
        if len(call.args) != len(definition.params):
            issues.append({
                'type': 'parameter_count_mismatch',
                'function': call.function_name,
                'expected': len(definition.params),
                'actual': len(call.args)
            })

        # Check parameter names (for keyword args)
        for arg_name in call.kwargs:
            if arg_name not in definition.param_names:
                issues.append({
                    'type': 'undefined_parameter',
                    'function': call.function_name,
                    'parameter': arg_name
                })

    return issues

Quality Assurance Patterns

Quality Score Calculation

Quality Score (0-100):

Code Quality (40 points):
โ”œโ”€ Syntax correctness (10)
โ”œโ”€ Style compliance (10)
โ”œโ”€ Code complexity (10)
โ””โ”€ Best practices (10)

Test Quality (30 points):
โ”œโ”€ Test coverage (15)
โ”œโ”€ Test success rate (10)
โ””โ”€ Test quality (5)

Documentation Quality (20 points):
โ”œโ”€ Docstrings (10)
โ”œโ”€ Comments (5)
โ””โ”€ Examples (5)

Security Quality (10 points):
โ”œโ”€ No vulnerabilities (5)
โ”œโ”€ Secure patterns (5)

Thresholds:
โ”œโ”€ 85-100: Excellent (production-ready)
โ”œโ”€ 70-84: Good (acceptable)
โ”œโ”€ 50-69: Fair (needs improvement)
โ””โ”€ 0-49: Poor (not acceptable)

Auto-Fix Priority System

Fix Priority Order:

Priority 1 (Always fix):
โ”œโ”€ Syntax errors
โ”œโ”€ Import errors
โ”œโ”€ Undefined variables
โ”œโ”€ Type errors (obvious)
โ””โ”€ Success rate: 95%+

Priority 2 (Usually fix):
โ”œโ”€ Style violations
โ”œโ”€ Missing docstrings
โ”œโ”€ Unused imports
โ”œโ”€ Simple complexity issues
โ””โ”€ Success rate: 80-95%

Priority 3 (Suggest fix):
โ”œโ”€ Complex refactoring
โ”œโ”€ Performance optimizations
โ”œโ”€ Architecture improvements
โ””โ”€ Success rate: 60-80%

Priority 4 (Report only):
โ”œโ”€ Design decisions
โ”œโ”€ Major refactoring
โ”œโ”€ Architectural changes
โ””โ”€ Requires human judgment

Testing Strategies for Autonomous Development

Test Generation Priorities

Test Priority Matrix:

Critical Path Tests (Must have):
โ”œโ”€ Core functionality tests
โ”œโ”€ Error handling tests
โ”œโ”€ Edge case tests
โ””โ”€ Coverage target: 100%

Integration Tests (Should have):
โ”œโ”€ Component integration
โ”œโ”€ External service integration
โ”œโ”€ End-to-end workflows
โ””โ”€ Coverage target: 80%

Performance Tests (Nice to have):
โ”œโ”€ Load tests
โ”œโ”€ Stress tests
โ”œโ”€ Benchmark tests
โ””โ”€ Coverage target: 50%

Test-First Development Pattern

For autonomous development:

1. Generate Test Cases First
   - Based on requirements
   - Cover happy path and edge cases
   - Include error scenarios

2. Implement to Pass Tests
   - Write minimal code to pass
   - Refactor after passing
   - Maintain test coverage

3. Expand Tests as Needed
   - Add tests for bugs found
   - Add tests for edge cases discovered
   - Keep tests up-to-date

Requirements Verification Patterns

Acceptance Criteria Validation

Verification Checklist Template:

Functional Requirements:
โ”œโ”€ [ ] Feature X implemented
โ”œโ”€ [ ] Feature Y working
โ”œโ”€ [ ] All specified behaviors present
โ””โ”€ [ ] Edge cases handled

Non-Functional Requirements:
โ”œโ”€ [ ] Performance targets met
โ”œโ”€ [ ] Security requirements satisfied
โ”œโ”€ [ ] Scalability considered
โ””โ”€ [ ] Maintainability ensured

Quality Requirements:
โ”œโ”€ [ ] Tests passing (100%)
โ”œโ”€ [ ] Code quality โ‰ฅ 85/100
โ”œโ”€ [ ] Documentation complete
โ””โ”€ [ ] No critical issues

User Experience:
โ”œโ”€ [ ] Easy to use
โ”œโ”€ [ ] Clear error messages
โ”œโ”€ [ ] Good documentation
โ””โ”€ [ ] Examples provided

Integration with Learning System

Pattern Storage for Development

{
  "dev_pattern": {
    "requirement_type": "mqtt_integration",
    "complexity": "medium",

    "successful_approach": {
      "milestone_count": 5,
      "milestone_sequence": [
        "dependencies",
        "core_logic",
        "integration",
        "testing",
        "documentation"
      ],
      "avg_milestone_time": 9.7,
      "total_time": 48.5
    },

    "common_issues": [
      {
        "issue": "certificate_path_mismatch",
        "frequency": 0.65,
        "fix": "use_relative_paths",
        "success_rate": 0.95
      },
      {
        "issue": "connection_timeout",
        "frequency": 0.45,
        "fix": "add_retry_logic",
        "success_rate": 0.88
      }
    ],

    "quality_metrics": {
      "avg_code_quality": 92,
      "avg_test_coverage": 91,
      "avg_security_score": 94
    },

    "skill_effectiveness": {
      "code-analysis": 0.94,
      "testing-strategies": 0.91,
      "security-patterns": 0.88
    }
  }
}

Best Practices

DO's

โœ… Break Down Complexity

  • Decompose requirements into small, manageable milestones
  • Each milestone should be independently testable
  • Commit each working milestone

โœ… Validate Continuously

  • Run tests after each change
  • Check parameter consistency frequently
  • Validate type safety throughout

โœ… Debug Systematically

  • Start with high-confidence fixes
  • Use pattern-based approaches
  • Learn from failures

โœ… Document Progressively

  • Document as you implement
  • Keep documentation synchronized
  • Include usage examples

โœ… Learn from Experience

  • Store successful patterns
  • Record failed approaches
  • Optimize based on learnings

DON'Ts

โŒ Don't Skip Validation

  • Never commit without tests passing
  • Don't ignore parameter mismatches
  • Don't skip quality checks

โŒ Don't Implement Everything at Once

  • Avoid big-bang implementation
  • Don't commit non-working code
  • Don't skip incremental commits

โŒ Don't Ignore Patterns

  • Don't repeat failed approaches
  • Don't ignore learned patterns
  • Don't make same mistakes twice

โŒ Don't Compromise Quality

  • Don't accept quality score < 70
  • Don't skip security validation
  • Don't skip documentation

Advanced Patterns

Parallel Milestone Execution

When milestones are independent:

Sequential (slower):
Milestone 1 โ†’ Milestone 2 โ†’ Milestone 3
Total time: 30 minutes

Parallel (faster):
Milestone 1 โ”€โ”
Milestone 2 โ”€โ”ผโ†’ Sync โ†’ Milestone 4
Milestone 3 โ”€โ”˜
Total time: 12 minutes

Use parallel execution for:
- Independent components
- Test generation
- Documentation updates
- Multiple bug fixes

Adaptive Planning Pattern

Adjust plan based on execution:

Initial Plan:
โ”œโ”€ Milestone 1: 15 min (estimated)
โ”œโ”€ Milestone 2: 20 min (estimated)
โ”œโ”€ Milestone 3: 15 min (estimated)
โ””โ”€ Total: 50 minutes

After Milestone 1 (took 25 min):
โ”œโ”€ Reason: Unexpected complexity
โ”œโ”€ Adjust remaining estimates: +10 min each
โ”œโ”€ New total: 70 minutes
โ””โ”€ Re-evaluate approach if needed

The Autonomous Development skill provides comprehensive guidance for managing full development lifecycles with minimal human intervention, ensuring high quality and continuous improvement through learning.

Score

Total Score

70/100

Based on repository quality metrics

โœ“SKILL.md

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