Debug Loop
Use when debugging a failing test or runtime error with hypothesis-driven investigation, autonomous command validation, and systematic root cause elimination.
Install
$ agentstack add skill-proffesor-for-testing-agentic-qe-debug-loop ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-proffesor-for-testing-agentic-qe-debug-loop) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Debug Loop
Autonomous hypothesis-driven debugging against real data. No guessing, no simulating.
Arguments
- `` — Description of the bug or unexpected behavior. If omitted, prompt the user.
Phases
Phase 1 — Reproduce
Run the exact command that shows the bug. Capture and display the REAL output. Confirm the bug is visible.
If the bug cannot be reproduced, stop and explain what was tried.
Phase 2 — Hypothesize and Test (up to 5 iterations)
For each iteration:
- State a specific hypothesis (e.g., "the query targets v2 tables but data is in v3 tables")
- Run a REAL command to test it (e.g.,
sqlite3 [db path] '.tables'thenSELECT COUNT(*) FROM [table]) - Record whether the hypothesis was confirmed or rejected
- If rejected, form the next hypothesis based on what you learned
Do NOT make code changes until you have a confirmed root cause.
Important checks:
- Always check both v2 and v3 SQLite tables when data issues are suspected
- Check dependency versions (e.g., sqlite3 vs better-sqlite3)
- Check for hardcoded values that may have been missed
Phase 3 — Fix
Make the minimal targeted fix. Explain:
- What the root cause was
- What you're changing and why
- What the blast radius is (which other code paths are affected)
Before applying, grep for ALL instances of the problematic pattern across the entire codebase.
Phase 4 — Verify
Run the SAME reproduction command from Phase 1. The output must now show correct values. If it doesn't, go back to Phase 2.
Show before/after output comparison.
Phase 5 — Regression
npm testRun the full test suite. If tests fail, fix them before committing.
Rules
- NEVER guess or simulate output — always run real commands
- NEVER make code changes before confirming root cause
- Always check for the pattern across the entire codebase, not just one file
- If blocked after 5 hypotheses, stop and ask the user for guidance
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: proffesor-for-testing
- Source: proffesor-for-testing/agentic-qe
- License: MIT
- Homepage: https://agentic-qe.dev/
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.