Hypothesis-driven autonomous debugging with real command validation

MITAuto-check passedDevelopment

Install Qe Debug Loop

skills CLI
$ npx skills add proffesor-for-testing/agentic-qe --skill qe-debug-loop -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install proffesor-for-testing/agentic-qe qe-debug-loop --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/proffesor-for-testing/agentic-qe.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.kiro/skills/qe-debug-loop .claude/skills/qe-debug-loop && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
qe-debug-loop
GitHub stars
494
Token cost
~519 tokens
SKILL.md length
304 words
Files
1
Skills in repo
111
Repo updated
First seen
Licence
MIT

At a glance

Hypothesis-driven autonomous debugging with real command validation

  • Works in 5 steps: Reproduce → Hypothesize and Test (up to 5 iterations) → Fix → …
  • Tasks that involve Debugging
  • SKILL.md covers Arguments, Phases and Rules
  • Calls npm and sqlite3

What it does

Qe Debug Loop is an agent skill from proffesor-for-testing/agentic-qe. Hypothesis-driven autonomous debugging with real command validation

Its SKILL.md is about 520 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Debugging. It works with SQLite. The repository describes itself as: Agentic QE Fleet is an open-source AI-powered QA/QE platform designed for use with Coding Agents (works best with Claude Code) featuring specialized agents and skills to support… The licence is MIT.

When your agent uses it

  • Tasks that involve Debugging

Example prompts

  • “/qe-debug-loop”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Reproduce
  2. Hypothesize and Test (up to 5 iterations)
  3. Fix
  4. Verify
  5. Regression

What it can do on your machine

Read from SKILL.md and the folder at commit 829d030. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npm
    • sqlite3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npm, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Qe Debug Loop loads about 519 tokens when it runs. Until then it costs about 20 tokens; SKILL.md has 304 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~20
When it runs · the whole SKILL.md, loaded when a task matches
~519

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from proffesor-for-testing/agentic-qe at commit 829d030, republished under its MIT licence (© proffesor-for-testing). 304 words, ~519 tokens.

Download SKILL.mdSave it as .claude/skills/qe-debug-loop/SKILL.md (or your agent's skills folder).
name
qe-debug-loop
description
Hypothesis-driven autonomous debugging with real command validation
inclusion
auto

Debug Loop

Autonomous hypothesis-driven debugging against real data. No guessing, no simulating.

Arguments

  • <symptom> — 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:

  1. State a specific hypothesis (e.g., "the query targets v2 tables but data is in v3 tables")
  2. Run a REAL command to test it (e.g., sqlite3 [db path] '.tables' then SELECT COUNT(*) FROM [table])
  3. Record whether the hypothesis was confirmed or rejected
  4. 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
bash
npm test

Run 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

© proffesor-for-testing, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .kiro/skills/qe-debug-loop of proffesor-for-testing/agentic-qe.

Open the folder on GitHubat commit 829d030

Compare with similar skills

Qe Debug Loop next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Qe Debug Loop compared with similar skills
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RoamCranot/roam-code517—~2.4kAutomated safety check: PassApache-2.0
Debugging MarchatCod-e-Codes/marchat137—~668Automated safety check: NotesMIT
Burla Internals Deep DiveBurla-Cloud/burla263—~2.4kAutomated safety check: PassCustom licence
Memorywhale Debuggingwuisabel-gif/MemWhale151—~370Automated safety check: PassMIT

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Works with

Categories

Questions about Qe Debug Loop

What does Qe Debug Loop do?

Hypothesis-driven autonomous debugging with real command validation. Qe Debug Loop is an agent skill from proffesor-for-testing/agentic-qe.

When should I use Qe Debug Loop?

Qe Debug Loop fits situations like: tasks that involve Debugging.

How do I install Qe Debug Loop in Claude Code?

Run `npx skills add proffesor-for-testing/agentic-qe --skill qe-debug-loop -a claude-code`. Or copy the skill folder (.kiro/skills/qe-debug-loop in proffesor-for-testing/agentic-qe) into .claude/skills/qe-debug-loop in your project. Claude Code loads it when a task matches its description.

How do I install Qe Debug Loop in Codex?

Run `npx skills add proffesor-for-testing/agentic-qe --skill qe-debug-loop -a codex`. Or copy the skill folder (.kiro/skills/qe-debug-loop in proffesor-for-testing/agentic-qe) into .agents/skills/qe-debug-loop in your project. Codex loads it when a task matches its description.

Can I use Qe Debug Loop in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add proffesor-for-testing/agentic-qe --skill qe-debug-loop -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/qe-debug-loop, .gemini/skills/qe-debug-loop, .github/skills/qe-debug-loop and .opencode/skills/qe-debug-loop in your project.

What does Qe Debug Loop need to run?

Going by SKILL.md and its folder, Qe Debug Loop needs the command-line tools its instructions call (npm and sqlite3).

Does Qe Debug Loop access the network?

SKILL.md contains no URLs. Its commands use npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Qe Debug Loop safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Qe Debug Loop use?

Qe Debug Loop is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Qe Debug Loop use?

About 519 tokens (SKILL.md is roughly 2.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Qe Debug Loop?

Skills that share tags, products or a category with Qe Debug Loop: Misakanet Failure Memory (Ikalus1988/MisakaNet, 524 stars), Roam (Cranot/roam-code, 517 stars), Debugging Marchat (Cod-e-Codes/marchat, 137 stars) and Burla Internals Deep Dive (Burla-Cloud/burla, 263 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Qe Debug Loop?

proffesor-for-testing (a GitHub user) maintains it in proffesor-for-testing/agentic-qe, which has 494 GitHub stars. The repository holds 111 skills in this directory. The repository was last updated on October 4, 2026.

Source: proffesor-for-testing/agentic-qe on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.