# NeoCoder Workflow Templates Analysis
## Template System Overview
NeoCoder's template system is a core feature that provides structured guidance for AI assistants. Templates are stored in Neo4j as `:ActionTemplate` nodes and define step-by-step workflows for common development tasks.
Each template includes:
- Unique keyword identifier (e.g., 'FIX', 'REFACTOR')
- Version information
- Detailed steps
- Complexity and effort estimates
- Verification requirements
## Template Structure
Templates are defined in Cypher files in the `/templates` directory and loaded into Neo4j during initialization. The typical structure of a template includes:
1. **Creation/Update** - MERGE operation to create or update the template
2. **Metadata** - Setting properties like version, complexity, etc.
3. **Steps** - Detailed markdown-formatted instructions
4. **Versioning** - Ensuring only one current version exists
Example structure from `fix_template.cypher`:
```cypher
// Create or update FIX template
MERGE (t:ActionTemplate {keyword: 'FIX', version: '1.2'})
ON CREATE SET t.isCurrent = true
ON MATCH SET t.isCurrent = true
SET t.description = 'Guidance on fixing a reported bug...'
SET t.complexity = 'MEDIUM'
SET t.estimatedEffort = 45
SET t.steps = '...'
// Make sure this is the only current version
MATCH (old:ActionTemplate {keyword: 'FIX', isCurrent: true})
WITH old.version <> '1.2'
SET old.isCurrent = false
```
## Available Templates
### FIX Template
**Purpose:** Guide AI assistants through fixing a reported bug.
**Key Steps:**
1. Identify context by reviewing project README
2. Reproduce and isolate the bug
3. Write a failing test demonstrating the bug
4. Implement the fix
5. Verify with tests (critical step)
6. Log successful execution
7. Update project artifacts
8. Assess risks
**Notable Features:**
- Emphasizes test-driven approach with failing test
- Strict verification requirements before proceeding
- Structured logging of successful fixes
- Risk assessment component
### REFACTOR Template
**Purpose:** Guide refactoring of code while maintaining functionality.
**Key Steps:**
1. Identify refactoring target and scope
2. Assess current structure and issues
3. Plan the refactoring approach
4. Ensure tests exist for current functionality
5. Execute refactoring in small, incremental steps
6. Verify with tests after each step
7. Document changes and rationale
8. Log successful completion
**Notable Features:**
- Emphasis on incremental changes
- Test-driven verification after each step
- Documentation of rationale for changes
### FEATURE Template
**Purpose:** Guide implementation of new features.
**Key Steps:**
1. Define feature requirements and scope
2. Plan the implementation approach
3. Design the API/interface first
4. Write tests for the new feature
5. Implement the feature
6. Verify functionality with tests
7. Document the new feature
8. Log successful completion
**Notable Features:**
- API-first design approach
- Test-driven development
- Documentation requirements
### DEPLOY Template
**Purpose:** Guide deployment of code to production.
**Key Steps:**
1. Verify pre-deployment status
2. Check deployment prerequisites
3. Prepare deployment artifacts
4. Execute deployment process
5. Verify deployment success
6. Monitor for post-deployment issues
7. Document deployment details
8. Log successful completion
**Notable Features:**
- Safety checks before deployment
- Monitoring requirements
- Rollback considerations
### TOOL_ADD Template
**Purpose:** Guide adding new tool functionality to NeoCoder.
**Key Steps:**
1. Define tool requirements and interface
2. Design the tool API
3. Implement the tool in appropriate module
4. Add appropriate error handling
5. Write tests for the tool
6. Document the tool functionality
7. Register the tool with the MCP server
8. Log successful completion
**Notable Features:**
- Interface design focus
- Registration with tool registry
- Documentation requirements
### CODE_ANALYZE Template
**Purpose:** Guide code analysis using AST/ASG tools.
**Key Steps:**
1. Identify analysis targets and scope
2. Select appropriate analysis tools
3. Set up analysis configuration
4. Execute analysis
5. Process and store results
6. Generate insights from analysis
7. Document findings and recommendations
8. Log successful completion
**Notable Features:**
- Integration with AST/ASG tools
- Insight generation
- Storage of analysis results in Neo4j
## Common Patterns
Across all templates, several common patterns emerge:
1. **Test-Driven Approach**
- Most templates emphasize writing tests first
- All require verification with tests before completion
2. **Incremental Steps**
- Tasks are broken down into manageable increments
- Changes are verified at each step
3. **Documentation Requirements**
- All templates include documentation steps
- Changes must be documented for future reference
4. **Workflow Logging**
- All templates require logging successful completion
- This creates an audit trail in the Neo4j graph
5. **Critical Verification Gates**
- Templates include "must-pass" verification steps
- AI assistants are instructed not to proceed if verification fails
## Implementation Details
Templates are implemented as:
1. **Cypher Files** - Source files in `/templates` directory
2. **Neo4j Nodes** - Loaded into Neo4j as `:ActionTemplate` nodes
3. **Markdown Content** - Steps are stored as markdown text
4. **Versioning** - Only one current version per template type
The AI assistant interacts with templates by:
1. Identifying the needed template by keyword
2. Querying Neo4j for the current version
3. Following the steps in the template
4. Logging completion back to Neo4j
## Extension Opportunities
The template system can be extended in several ways:
1. **New Templates** - Adding templates for other common tasks
2. **Template Parameters** - Adding support for parameterized templates
3. **Template Combinations** - Allowing templates to reference other templates
4. **Conditional Steps** - Adding conditional logic in templates
5. **Feedback Loop** - Collecting success metrics on template effectiveness
## Effectiveness Assessment
The template system is particularly effective for:
1. **Standardization** - Ensuring consistent workflows
2. **Quality Assurance** - Enforcing testing and verification
3. **Knowledge Management** - Capturing best practices
4. **Audit Trail** - Tracking work completed
5. **Onboarding** - Helping new AI assistants follow project standards
The step-by-step format works well with AI assistants' workflow, providing clear guidance while allowing flexibility in implementation details.
