Skip to content
Skillpedia
Agents48k · #2056

agent-qa-debug-fix

Fixes errors in AI agent tests. It analyzes test results, finds problems, and helps fix the code. Ensures agents work without failures.

What it does

This agent fixes failed program tests. It analyzes evidence from a failed test, like logs and files, and makes the smallest necessary code change to fix the issue, without hiding real defects.

When to use it

  • ✓When a program test fails and needs fixing.
  • ✓If logs and files indicate an error in the test, program, or environment.
  • ✓To verify if a small fix works before running all tests.

Example of what to ask your AI

“Fix the failed test in the staging environment, using the available information.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/agent-qa-debug-fix/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/agent-qa-debug-fix/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The agent first collects all information about the failed test. Then, it analyzes this information to understand the cause of the error and makes the smallest possible change to the code or configuration to fix it, without creating new problems.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add sickn33/agentic-awesome-skills --skill agent-qa-debug-fix

Or download just the file:

curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/agent-qa-debug-fix/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

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.
FAQ

What are 'Agent QA runs'?

These are automated test executions to check if a program is working correctly.

What do 'debug' and 'patch' mean?

'Debug' means finding and fixing errors. 'Patch' means applying a small fix to a program.

Can I use this agent to make big changes to the program?

No, this agent is designed only to make the smallest fix needed for a specific failed test, without altering other parts of the program.

Details

Original description by the author

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

repo: sickn33/agentic-awesome-skills

Popularity

GitHub stars
48k
Ranking position
#2056
License
MIT
Updated
10/15/2026

Is this skill useful?

0

Sign in to vote.

Comments

  • …

More skills from this repository

Similar skills