Systematic Debugging
PassAudited by VirusTotal on May 11, 2026.
Overview
Type: OpenClaw Skill Name: runesleo-systematic-debugging Version: 3.0.0 The skill bundle defines a systematic debugging framework for an AI agent, emphasizing root cause analysis over quick fixes. It utilizes standard, non-destructive commands such as `grep` and `git log` for context gathering (SKILL.md) and does not contain any executable code or instructions for data exfiltration, persistence, or unauthorized access.
Findings (0)
Artifact-based informational review of SKILL.md, metadata, install specs, static scan signals, and capability signals. ClawScan does not execute the skill or run runtime probes.
The agent may read project files and history as part of debugging.
The skill encourages local repository inspection and git history review. These are normal debugging actions, but users should ensure the agent is working in the intended project scope.
Search codebase for similar error patterns: `grep -r "ErrorType" .` ... Check git log for related recent changes: `git log --oneline -20`
Use the skill within the intended repository and avoid granting broader filesystem access than needed.
Debug output could expose sensitive application data if used carelessly, especially outside a local test environment.
Adding diagnostic logging is purpose-aligned for debugging, but logs can accidentally include sensitive values if not scoped or redacted.
BEFORE proposing fixes, add diagnostic instrumentation: ... Log what data enters component ... Log what data exits component
Keep diagnostics temporary, prefer local or test environments, and redact secrets or personal data from logs.
The agent may rely on prior notes or conversations when deciding how to debug or fix an issue.
The skill tells the agent to consult and later update persistent or prior context. That is useful for debugging, but such context can be stale, incomplete, or contain sensitive details.
Check project docs, MEMORY files, or past conversations ... remember to record solution later
Verify recalled context against current project evidence before applying it, and avoid storing sensitive incident details unnecessarily.