sf-agent-framework
Version:
AI Agent Orchestration Framework for Salesforce Development - Two-phase architecture with 70% context reduction
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Markdown
# Execute Checklist Task
This task provides a sophisticated checklist validation system with multi-level
quality assurance, star ratings, and actionable feedback.
## Purpose
Enable agents to execute quality checklists that:
- Validate work against defined criteria
- Provide star ratings for nuanced assessment
- Offer ready/not-ready determinations
- Generate improvement recommendations
- Track quality trends over time
## Checklist Levels
### 1. Basic Validation (Level 1)
- Essential completeness checks
- Binary pass/fail criteria
- Minimum viable quality
### 2. Comprehensive Review (Level 2)
- Detailed quality assessment
- Star ratings (1-5) for each criterion
- Specific improvement suggestions
### 3. Expert Assessment (Level 3)
- Advanced domain-specific evaluation
- Best practice validation
- Excellence criteria
- Innovation opportunities
## Execution Process
### Step 1: Checklist Selection
```
1. Identify appropriate checklist for context
2. Load from checklists/ directory
3. Determine validation level needed
4. Parse checklist structure
```
### Step 2: Item Evaluation
For each checklist item:
```
1. Present criterion clearly
2. Evaluate against current work
3. Assign rating or pass/fail
4. Document specific observations
5. Note improvement opportunities
```
### Step 3: Rating Systems
**Binary Assessment**:
- ✅ Pass - Criterion fully met
- ❌ Fail - Criterion not met
- ⚠️ Partial - Needs attention
**Star Rating Assessment**:
- ⭐ (1/5) - Significant issues, immediate action needed
- ⭐⭐ (2/5) - Below standard, improvements required
- ⭐⭐⭐ (3/5) - Meets minimum requirements
- ⭐⭐⭐⭐ (4/5) - Good quality, minor improvements possible
- ⭐⭐⭐⭐⭐ (5/5) - Excellent, best practice example
### Step 4: Overall Assessment
**Ready/Not Ready Determination**:
```
READY FOR NEXT PHASE when:
- All critical items pass
- Average star rating ≥ 3.5
- No blocking issues identified
NOT READY when:
- Any critical item fails
- Average star rating < 3.5
- Blocking issues present
```
### Step 5: Generate Feedback
**Improvement Recommendations**:
1. **Critical** - Must fix before proceeding
2. **Important** - Should address soon
3. **Suggested** - Would enhance quality
4. **Optional** - Nice to have improvements
**Feedback Format**:
```markdown
## Checklist Results: [Checklist Name]
### Overall Rating: [X.X/5.0 stars] - [READY/NOT READY]
### Strengths:
- [What was done well]
### Areas for Improvement:
- **Critical**: [Must fix items]
- **Important**: [Should fix items]
- **Suggested**: [Enhancement opportunities]
### Next Steps:
1. [Specific action items in priority order]
```
## Integration with Agents
### Pre-Execution
- Agent completes work to be validated
- Identifies appropriate checklist
- Prepares context for evaluation
### During Execution
- Agent can provide self-assessment
- Interactive validation with user
- Real-time feedback incorporation
### Post-Execution
- Results integrated into workflow
- Blocking issues prevent progression
- Quality trends tracked over time
## Advanced Features
### Conditional Criteria
```
IF project_type == "enterprise" THEN
Additional security criteria apply
END IF
```
### Weighted Scoring
```
Security Items: Weight = 2.0
Performance Items: Weight = 1.5
Documentation: Weight = 1.0
```
### Progressive Validation
- Start with Level 1 for drafts
- Level 2 for review ready
- Level 3 for production ready
## Success Metrics
- Validation completed thoroughly
- Accurate ratings assigned
- Actionable feedback provided
- Clear next steps identified
- Quality improvement over time
## Example Usage
```
Agent: "I've completed the Apex class. Let me run the code review checklist."
*Executes code-review-checklist.md*
Results:
- Security: ⭐⭐⭐⭐⭐ (5/5) - Excellent CRUD/FLS checks
- Testing: ⭐⭐⭐ (3/5) - Needs edge case coverage
- Performance: ⭐⭐⭐⭐ (4/5) - Good, consider bulkification
- Documentation: ⭐⭐ (2/5) - Missing method comments
Overall: 3.5/5 - NOT READY
Critical: Add test coverage for null inputs
Important: Document all public methods
```