An automated code auto-diagnosis and fix skill designed to systematically resolve compiler, runtime, and logical bugs.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install code-fix
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 code-fix 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 Code Error Fixer?
The Code Error Fixer is a highly structural engineering skill optimized for troubleshooting software vulnerabilities, compilation failures, runtime crashes, and dependency anomalies. Built on advanced engineering practices such as Root Cause Analysis (RCA), the Scientific Method, and Rubber Duck Debugging, this agent protocol bypasses guesswork in favor of a strict, execution-driven workflow. It ensures that developers can seamlessly eliminate unexpected behavior across modern development stacks.
By adding this extension to Openclaw Skills, engineering teams deploy an autonomous agent capable of inspecting environments, isolating problematic stack traces, querying package managers, and executing precise programmatic modifications. It acts as an elite virtual debugger that avoids erratic code mutation, selecting the least intrusive, highest-impact modifications to achieve operational stability.
Code Error Fixer Use Cases
- User encounters syntax errors, compilation failures, type mismatches, or runtime stack traces.
- Automated test suites report regression bugs or application configuration failures.
- Unexpected behavior or logical silent bugs occur where an application operates without explicitly crashing.
- Third-party packages present dependency resolution failures or environment constraints.
- Developer explicitly queries for assistance with questions such as "why is this not working" or "help me debug this error".
How Code Error Fixer Works
- Reproduce: The skill reads crash logs, samples runtime constraints (such as running
node --versionorpython --version), and establishes a Minimal Reproducible Example (MRE) to guarantee a stable error context. - Isolate: Using systematic strategies like binary search code isolation, differential analysis (
git diff), or diagnostic logging injections, the agent zeroes in on the exact file, block, or variable triggering the exception. - Understand: The agent synthesizes expected vs. actual performance behaviors, referencing API docs or executing web queries to confirm historical bugs or dependency updates before touching code.
- Fix: Applying the principle of minimal intervention, the skill writes precise micro-adjustments or defensive checks directly to the destination codebase without provoking structural regressions.
- Verify: The engine retraces the reproduction steps, compiles the software, runs existing test suites, and monitors linting validations to ensure comprehensive resolution.
Code Error Fixer Setup
Integrate this capability directly into your workspace. Ensure your runtime environment exposes the necessary tool paths required for system inspection:
# Ensure Openclaw agent environment has access to allowed CLI tools
which grep bash npx cargo pipdeptree go
# To verify dependencies for Node.js workflows
npm ls <package-name>
# To evaluate underlying environment errors in Python setups
pipdeptree -p <package-name>
Code Error Fixer Data Schema & Taxonomy
The skill manages diagnosis state parameters and executes structural troubleshooting using specific platform diagnostic trees. It coordinates resolution mapping using the following taxonomy rules:
| Error Domain | Diagnostic Targets | Core Command Reference |
|---|---|---|
| JavaScript / TypeScript | node_modules, package.json, tsconfig.json |
node --version && npx tsc --version |
| Python Environments | Virtual environments, global site-packages | python --version && which python |
| Go Frameworks | go.mod, dependency graphs |
go mod graph, go mod tidy |
| Rust Toolchains | Cargo crates, compiler configurations | cargo tree, cargo clean && cargo build |
All diagnostic outputs obey explicit conversational messaging states, tracing from early confirmation (Error Reproduction), down through root cause identification (Root Cause Statement), up to ultimate testing execution (Verification Verdict).
Code Error Fixer Advanced Features
- Strict multi-platform dependency analysis using specialized deep inspection routines (
pipdeptree,npm ls, andcargo tree). - Multi-tiered isolation mechanics containing an automatic bisection protocol to locate runtime errors in extensive codebases.
- Inherent support for Minimal Reproducible Example (MRE) generation frameworks.
- Built-in defensive coding verification constraints that prevent the agent from applying arbitrary dependency updates or structural refactors without verified root causes.
SKILL.md
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