A disciplined 8-step framework designed to prevent AI coding agents from falling into hallucination loops by enforcing test-driven diagnosis and root cause analysis.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install bug-fix-protocol
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install bug-fix-protocol using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Bug Fix Protocol?
The Bug Fix Protocol is a rigorous technical standard for AI coding agents that prioritizes the integrity of the test system over quick fixes. Grounded in the philosophy that a production bug is fundamentally a failure of the safety net, this skill mandates that every bug fix includes both a code patch and an improvement to the testing suite. By using this methodology within the Openclaw Skills ecosystem, developers can eliminate the common fix loop where AI agents guess at solutions without understanding the underlying failure.
This protocol transforms bug fixing from a reactive task into a proactive strengthening of the entire codebase. It treats the test system as the primary line of defense, ensuring that any bug that reaches production results in a permanent upgrade to the diagnostic capabilities of the project. This makes it an essential part of any library of Openclaw Skills for professional software development.
Bug Fix Protocol Use Cases
- Resolving complex logic errors where the agent is stuck in a repetitive hallucination cycle.
- Improving the reliability of legacy codebases through disciplined test-driven development.
- Ensuring that bugs fixed by AI agents do not regress in future deployments.
- Auditing existing test systems to identify blind spots in the CI/CD pipeline.
How Bug Fix Protocol Works
- The agent analyzes the reported symptom to understand exactly what broke without guessing.
- A reproduction test is written to confirm the bug, ensuring the test fails (Red) before any code is changed.
- The agent performs a root cause analysis to find the source of the problem, not just the symptom.
- A minimal, high-integrity fix is designed to address the root cause without creating technical debt.
- Changes are applied strictly to relevant code sections to avoid unnecessary side effects.
- The test suite is verified to ensure the reproduction test is now Green and no neighbor tests are broken.
- A deep review is conducted to find and fix similar patterns or vulnerabilities elsewhere in the repository.
- The test system is audited to identify why the bug was missed and how to prevent that entire class of bugs.
Bug Fix Protocol Setup
To implement this within your environment, include the protocol markdown in your agent's knowledge base. Ensure your development environment has a functioning test runner compatible with your stack.
# Example of initializing a test suite for the protocol
npm test -- --watch
# or for Python environments
pytest
Configure your agent to strictly follow the 8-step checklist provided in the Openclaw Skills documentation before committing any code changes.
Bug Fix Protocol Data Schema & Taxonomy
The skill organizes its output into two primary documentation formats to maintain a clear audit trail:
| Document Type | Purpose | Key Fields |
|---|---|---|
| Bug Fix Log | Documents the specific fix | Symptom, Root Cause, Solution, Test Status (Red/Green) |
| Test System Audit | Analyzes the failure of the safety net | Failure Reason, Improved Layers (Unit/E2E/Static), Action Items |
Metadata is tracked via file paths and specific test identifiers to ensure the fix is verifiable and reproducible.
Bug Fix Protocol Advanced Features
- Multi-layer testing support including Unit, Integration, E2E, and Visual regression tests.
- Automated deep review pattern matching to scan the entire codebase for similar architectural vulnerabilities.
- Structured audit logging to track the historical evolution of the test system reliability.
- Integration with static analysis tools like linters and type checkers to catch pattern-based errors early.
SKILL.md
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