Closed Loop Design Skill
Guide for designing closed-loop prompts that ensure agent reliability through feedback loops.
When to Use
- Designing new agentic workflows
- Adding validation to existing processes
- Creating self-correcting agent pipelines
- Building automated test-fix cycles
Core Concept
Every agentic operation should follow the Request-Validate-Resolve pattern:
REQUEST → VALIDATE → RESOLVE
↑ ↓
└────────────────────┘Design Workflow
Step 1: Identify the Operation
What task needs to be validated?
- Code changes (feature, bug fix, refactor)
- File operations (create, modify, delete)
- External interactions (API calls, database queries)
- Build/deploy operations
Step 2: Define Validation Mechanism
How do we know if it succeeded?
| Operation Type | Validation Mechanism |
|---|---|
| Code changes | Run tests, type check, lint |
| File operations | Verify file exists, check content |
| API interactions | Check response status, validate data |
| Build operations | Build succeeds, no errors |
Step 3: Design the Resolve Path
What happens on failure?
- Analyze: Parse error output to understand failure
- Fix: Make minimal, targeted corrections
- Re-validate: Run validation again
- Limit retries: Set maximum attempts (typically 3-5)
Step 4: Create the Prompt Structure
Template:
## Closed Loop: [Operation Name]
### Request
[Clear task description with success criteria]
### Validate
- Command: `[validation command]`
- Success: [what success looks like]
- Failure: [what failure looks like]
### Resolve (if validation fails)
1. Analyze the failure output
2. Identify root cause
3. Apply minimal fix
4. Return to Validate step
5. Maximum 3 retry attemptsExample: Test-Fix Loop
## Closed Loop: Implement Feature
### Request
Implement the user login feature according to spec.
### Validate
- Command: `pytest tests/test_auth.py -v`
- Success: All tests pass (exit code 0)
- Failure: One or more tests fail
### Resolve
1. Read failing test output
2. Identify which test failed and why
3. Fix the implementation (not the test)
4. Re-run pytest
5. Maximum 3 retry attemptsCommon Closed Loop Patterns
Code Quality Loop
REQUEST: Write/modify code
VALIDATE: Lint + Type check + Tests
RESOLVE: Fix errors iterativelyBuild Verification Loop
REQUEST: Make changes
VALIDATE: Full build succeeds
RESOLVE: Fix build errorsE2E Validation Loop
REQUEST: Implement user flow
VALIDATE: E2E test passes
RESOLVE: Fix failing stepsBest Practices
- Start with tests: If tests do not exist, consider adding them first
- Fast validation first: Run quick checks before slow ones
- Structured output: Use JSON for machine-parseable results
- Clear failure messages: Include context for resolution
- Bounded retries: Prevent infinite loops
Memory References
- @closed-loop-anatomy.md - Full pattern documentation
- @test-leverage-point.md - Why tests are ideal validators
- @validation-commands.md - Validation command patterns
Version History
- v1.0.0 (2025-12-26): Initial release
Last Updated
Date: 2025-12-26 Model: claude-opus-4-5-20251101