Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add iradoweck/antigravity-awesome-skills --skill agent-qa-debug-fixgit clone --depth 1 https://github.com/iradoweck/antigravity-awesome-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/iradoweck/antigravity-awesome-skills/agent-qa-debug-fix)<a href="https://agentmods.dev/skills/iradoweck/antigravity-awesome-skills/agent-qa-debug-fix"><img src="https://agentmods.dev/badge/skills/iradoweck/antigravity-awesome-skills/agent-qa-debug-fix/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/iradoweck/antigravity-awesome-skills/agent-qa-debug-fix"><img src="https://agentmods.dev/badge/skills/iradoweck/antigravity-awesome-skills/agent-qa-debug-fix.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00035 | $0.00885 |
| Opus 5 | $0.00017 | $0.00443 |
| Sonnet 5 | $0.00007 | $0.00177 |
| Haiku 4.5 | $0.00003 | $0.00089 |
Grade A, and why
agent-qa-debug-fix scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to agent-qa-debug-fix — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on 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
- Start with evidence collection:
agent_qa_get_runagent_qa_get_run_stepsagent_qa_get_run_artifactagent_qa_get_run_logsagent_qa_get_run_execution_logs
- Call
agent_qa_classify_failureand treat its category as a hypothesis, not a verdict. - Identify the failing surface: test definition, hook, application under test, runtime infrastructure, or agent behavior.
- Inspect the relevant local files directly. Do not infer patches from artifacts alone.
- Explain the evidence-to-change link, then apply the smallest code or YAML change that accounts for the evidence.
- Validate any changed Agent QA definition before execution.
- Re-run the narrowest affected Agent QA test, suite, hook, or unit test within the approved environment.
- Report the root cause, changed files, verification command or MCP action, result, and remaining risk.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 78 lines · 35 tokens per session scan A a3faa542300c
agent-qa-debug-fix is a skill published in the GitHub repository iradoweck/antigravity-awesome-skills (30 stars, last pushed 9d ago), licensed MIT. It adds 35 tokens to every session and 885 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to agent-qa-debug-fix, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
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.
agent-qa-result-triage
Triage failed Agent QA runs with MCP evidence, artifacts, logs, fixed failure categories, confidence, and actionable next steps.
qa-expert
Expert-level quality assurance, testing strategies, automation, and QA processes. Use when the user mentions testing, test automation, quality assurance, or Selenium, or when the task involves Testing Types, QA Processes, Test Strategy, or Defect Management.
agentic-review
Use when reviewing current branch for bugs before pushing or merging, when wanting a thorough multi-agent review of local changes, or when preparing work for human review. Not for codebase structure, not for code style, and not for fixing what it finds.
bug-analysis
A method for investigating confirmed software bugs by tracing their cause in code and assessing their effects. It also records repair and regression-testing recommendations in a test report.
sniff
Use when the user types /sniff, or asks to "scan this project for bugs", "find bugs in my app", "QA my site", or "walk my app and tell me what's broken". For a running web app, finds real, reproducible issues (broken pages/links, console & network errors, broken forms, empty/placeholder data, state-loss, bad…