Skip to content
cccskills
FreePublished on GitHub

agent-qa-debug-fix

Debug, patch, and verify failed Agent QA runs from MCP evidence, artifacts, logs, and local code without hiding product or infrastructure defects.

The English summary is being prepared. Showing the original description.

See how to install

Files included (2)

  • SKILL.md4.0 KB
  • SKILL_CN.md3.7 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Agent QA Debug Fix

Overview

Repair a failed Agent QA run from recorded evidence and the relevant local source. Treat the classifier as a hypothesis, make the smallest justified change, and verify the narrowest affected behavior without rewriting a test merely to conceal a real defect.

When to Use

  • A failed Agent QA run has already been triaged and now requires a code or YAML repair.
  • Artifacts and logs point to a test, hook, product, runtime, or agent-behavior defect.
  • A proposed fix must be verified with the narrowest Agent QA or unit-test rerun.
  • The user asks to self-heal or update a stale Agent QA definition from evidence.

Preconditions and Approval Boundary

  • Confirm the repository, workspace, target environment, and files the user authorizes you to modify.
  • Inspect the planned test's external side effects before rerunning it; obtain explicit confirmation for production-facing, destructive, or irreversible actions.
  • Preserve unrelated user changes and keep the patch limited to the evidenced failure.
  • Do not expose credentials or sensitive application data from artifacts and logs.

Workflow

  1. Start with evidence collection:
    • agent_qa_get_run
    • agent_qa_get_run_steps
    • agent_qa_get_run_artifact
    • agent_qa_get_run_logs
    • agent_qa_get_run_execution_logs
  2. Call agent_qa_classify_failure and treat its category as a hypothesis, not a verdict.
  3. Identify the failing surface: test definition, hook, application under test, runtime infrastructure, or agent behavior.
  4. Inspect the relevant local files directly. Do not infer patches from artifacts alone.
  5. Explain the evidence-to-change link, then apply the smallest code or YAML change that accounts for the evidence.
  6. Validate any changed Agent QA definition before execution.
  7. Re-run the narrowest affected Agent QA test, suite, hook, or unit test within the approved environment.
  8. Report the root cause, changed files, verification command or MCP action, result, and remaining risk.

Fix Rules

  • Do not invent selectors, screen states, screenshots, logs, or source files.
  • Do not rewrite a test merely to make it pass when the artifact shows a product or runtime defect.
  • Preserve canonical Agent QA IDs when editing tests, suites, hooks, or memory files.
  • Prefer agent_qa_validate_test, agent_qa_validate_suite, and agent_qa_validate_definition before rerunning edited YAML.
  • When MCP is unavailable, use dashboard REST APIs or local .agent-qa artifacts and state that MCP evidence was unavailable.
  • Stop and report the blocker when evidence cannot distinguish between materially different fixes.

Example

User: Fix the failed staging checkout run, but do not touch production.

Expected handling: collect the failed run evidence, classify it, inspect the implicated local
definition and application code, patch only the evidenced cause, validate, rerun the single
staging test, and report changed files plus remaining uncertainty.

Limitations

  • Requires access to the relevant run evidence and local source; artifacts alone may not establish root cause.
  • Cannot guarantee that an intermittent browser, device, network, or provider failure is fixed after one successful rerun.
  • Does not authorize production changes, data mutation, dependency installation, or broader refactoring beyond the user's approved scope.
  • A passing narrow rerun does not replace the repository's normal test suite or human review.

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Arquitecto de Soluciones Principal y Consultor Tecnológico de Andru.ia. Diagnostica y traza la hoja de ruta óptima para proyectos de IA en español.

The English summary is being prepared. Showing the original description.

lingxling/awesome-skills-cn316Updated Oct 7, 2026

007

Free

Security audit, hardening, threat modeling (STRIDE/PASTA), Red/Blue Team, OWASP checks, code review, incident response, and infrastructure security for any project.

The English summary is being prepared. Showing the original description.

lingxling/awesome-skills-cn316Updated Oct 7, 2026

Ingeniero de Sistemas de Andru.ia. Diseña, redacta y despliega nuevas habilidades (skills) dentro del repositorio siguiendo el Estándar de Diamante.

The English summary is being prepared. Showing the original description.

lingxling/awesome-skills-cn316Updated Oct 7, 2026

Estratega de Inteligencia de Dominio de Andru.ia. Analiza el nicho específico de un proyecto para inyectar conocimientos, regulaciones y estándares únicos del sector. Actívalo tras definir el nicho.

The English summary is being prepared. Showing the original description.

lingxling/awesome-skills-cn316Updated Oct 7, 2026

AI-powered presentation generation via the 2slides API — create slides from text, match a reference image style, summarize documents into decks, add AI voice narration, and export pages/audio. Use for any "make slides", "create a deck", or "slides from this document" request.

The English summary is being prepared. Showing the original description.

lingxling/awesome-skills-cn316Updated Oct 7, 2026

360 feedback register: reviewer, subject, review cycle, visibility, due date and score, as CSV, SQL, JSON Schema or Notion on request. Use for 360 reviews or peer feedback cycles.

The English summary is being prepared. Showing the original description.

lingxling/awesome-skills-cn316Updated Oct 7, 2026

See all skills by lingxling

Report a problem with this skill