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tomevault-io (@tomevault-io) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Closed Loop Design by tomevault-io — Agent Skill

Name: Closed Loop Design
Author: tomevault-io

Closed Loop Design

Design closed-loop prompts with Request-Validate-Resolve structure for reliable agentic workflows. Use when creating self-validating agents, adding feedback loops, or improving agent reliability through verification. Use when this capability is needed.

tomevault-io 934459d 2 files · 4.5 KB Updated Sep 17, 2026

File contents

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 attempts

Example: 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 attempts

Common Closed Loop Patterns

Code Quality Loop

REQUEST: Write/modify code
VALIDATE: Lint + Type check + Tests
RESOLVE: Fix errors iteratively

Build Verification Loop

REQUEST: Make changes
VALIDATE: Full build succeeds
RESOLVE: Fix build errors

E2E Validation Loop

REQUEST: Implement user flow
VALIDATE: E2E test passes
RESOLVE: Fix failing steps

Best 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

Converted and distributed by TomeVault — claim your Tome and manage your conversions.

---name: closed-loop-designdescription: Design closed-loop prompts with Request-Validate-Resolve structure for reliable agentic workflows. Use when creating self-validating agents, adding feedback loops, or improving agent reliability through verification. Use when this capability is needed.---# Closed Loop Design SkillGuide 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 ConceptEvery agentic operation should follow the Request-Validate-Resolve pattern:```textREQUEST → VALIDATE → RESOLVE ↑ ↓ └────────────────────┘```## Design Workflow### Step 1: Identify the OperationWhat 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 MechanismHow 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 PathWhat happens on failure?1. **Analyze**: Parse error output to understand failure2. **Fix**: Make minimal, targeted corrections3. **Re-validate**: Run validation again4. **Limit retries**: Set maximum attempts (typically 3-5)### Step 4: Create the Prompt StructureTemplate:```markdown## 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 output2. Identify root cause3. Apply minimal fix4. Return to Validate step5. Maximum 3 retry attempts```## Example: Test-Fix Loop```markdown## Closed Loop: Implement Feature### RequestImplement 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### Resolve1. Read failing test output2. Identify which test failed and why3. Fix the implementation (not the test)4. Re-run pytest5. Maximum 3 retry attempts```## Common Closed Loop Patterns### Code Quality Loop```textREQUEST: Write/modify codeVALIDATE: Lint + Type check + TestsRESOLVE: Fix errors iteratively```### Build Verification Loop```textREQUEST: Make changesVALIDATE: Full build succeedsRESOLVE: Fix build errors```### E2E Validation Loop```textREQUEST: Implement user flowVALIDATE: E2E test passesRESOLVE: Fix failing steps```## Best Practices1. **Start with tests**: If tests do not exist, consider adding them first2. **Fast validation first**: Run quick checks before slow ones3. **Structured output**: Use JSON for machine-parseable results4. **Clear failure messages**: Include context for resolution5. **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---> Converted and distributed by [TomeVault](https://tomevault.io/claim/melodic-software) — claim your Tome and manage your conversions.

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