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Qa Debugging

Listed
vasilyu1983·vlatest·testing·MIT

Identifies and suggests fixes for errors in QA test scripts using AI analysis and code suggestions.

Repository

Install on your platform

This skill no longer installs under the name qa-debugging. vasilyu1983/ai-agents-public is deleted or private, so it cannot be installed from.

We check each listing against its upstream repository with the rules the skills CLI uses, last on 2026-10-22. We don't show a command we know will fail.

Repository install instructions

What we know about this skill

Publisher

vasilyu1983

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 17 hosts that are neither well-known infrastructure nor declared in the skill's frontmatter: 12factor.net, agents.stackoverflow.com, api.stackexchange.com, developer.chrome.com, doc.rust-lang.org….

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

    Hosts contacted

    sre.googleundeclaredopentelemetry.ioundeclaredgithub.comsource hostwww.w3.orgstandards12factor.netundeclaredrr-project.orgundeclaredpernos.coundeclareddeveloper.chrome.comundeclarednodejs.orgdocumentationdocs.python.orgdocumentationdoc.rust-lang.orgundeclaredwww.kernel.orgundeclaredkubernetes.ioundeclaredwww.postgresql.orgundeclaredlangfuse.comundeclaredgenai.owasp.orgundeclaredsignoz.ioundeclaredgrafana.comundeclareddocs.sentry.ioundeclaredapi.stackexchange.comundeclaredagents.stackoverflow.comundeclared

    What it found (3 of 24)

    • skills/universal/qa-debugging/data/sources.json:15contacts sre.google
      "url": "https://sre.google/sre-book/effective-troubleshooting/",
    • skills/universal/qa-debugging/data/sources.json:22contacts sre.google
      "url": "https://sre.google/sre-book/managing-incidents/",
    • skills/universal/qa-debugging/data/sources.json:31contacts opentelemetry.io
      "url": "https://opentelemetry.io/docs/",

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned vasilyu1983/ai-agents-public at 3ee3637d25.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
3ee3637d25
Manifest
skills/universal/qa-debugging/SKILL.md
Scanned
22 files, 2,373 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The QA Debugging skill assists AI agents in systematically debugging errors found within QA test scripts. It guides the agent through a structured process of identifying root causes, suggesting fixes, and creating prevention plans. The skill emphasizes transforming observed symptoms into evidence-based solutions, including verification steps and regression tests to ensure long-term stability.

When to use it

  • When encountering unexpected errors or failures in QA test scripts.
  • To quickly isolate the cause of a bug by narrowing down potential sources (code path, feature flags, configuration).
  • For identifying and implementing fixes that address root causes rather than just symptoms.
  • To develop regression tests to prevent similar issues from recurring in the future.

Key capabilities

  • Failure Signature Capture: Collects essential information like error messages, stack traces, request IDs, timestamps, build SHAs, environment details, and affected users.
  • Hypothesis Ranking: Generates ranked hypotheses for potential root causes based on collected evidence.
  • Experiment Design: Suggests targeted experiments with expected outcomes to validate or disprove hypotheses.
  • Fix Option Generation: Proposes solutions addressing the identified root cause.
  • Regression Test Target Identification: Recommends appropriate layers (unit, integration, e2e) for creating regression tests.

Example prompts

  • "I'm seeing a 'TypeError: undefined is not an object' error in my test script. Can you help me debug it?"
  • "This test is failing intermittently; can you suggest ways to isolate the cause?"
  • "The QA test failed with this stack trace [paste stack trace]. What are some possible root causes and how should I verify them?"

Tips & gotchas

  • Reproducibility is key: Focus on reducing the issue to a minimal, reproducible input for effective debugging.
  • Root Cause Focus: The skill prioritizes fixing the underlying cause of errors rather than implementing temporary workarounds.
  • Structured Logging: For optimal results, ensure your test environment utilizes structured logs and correlation IDs.