A project-quality assurance skill that coordinates tests, user journeys, evidence, release checks, and feedback through the QAMESH project QA system. QA, or quality assurance, is the process of checking that software works as expected.

Use it to initialize, plan, run, release, document, and review project QA; run deterministic user journeys; collect evidence; and connect browser testing through Playwright when it is detected.

It gives project testing a defined flow from setup through release and keeps test evidence and repair feedback together. It also separates full QA journeys from quick post-deployment health checks.

auto-qa — Skill for Claude Code and Codex by Insajin

Install

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.

Any agent

npx skills add Insajin/autopus-adk --skill auto-qa

Clone the repo

git clone --depth 1 https://github.com/Insajin/autopus-adk

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/insajin/autopus-adk/auto-qa/github.svg)](https://agentmods.dev/skills/insajin/autopus-adk/auto-qa)

Your own site

<a href="https://agentmods.dev/skills/insajin/autopus-adk/auto-qa"><img src="https://agentmods.dev/badge/skills/insajin/autopus-adk/auto-qa/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/insajin/autopus-adk/auto-qa"><img src="https://agentmods.dev/badge/skills/insajin/autopus-adk/auto-qa.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,862 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

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	$0.00022	$0.02862
Opus 5	$0.00011	$0.01431
Sonnet 5	$0.00004	$0.00572
Haiku 4.5	$0.00002	$0.00286

Measured 5d ago against content hash 13199c11e66f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

auto-qa 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 5d 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.

.omp/skills/auto-qa/SKILL.md · 107 lines

How it starts

The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.

auto-qa — QAMESH Project QA Mesh

OMP Invocation

/auto qa ...
/auto-qa ...
Load detail skill auto-qa for either entrypoint.

프로젝트: autopus-adk | 모드: full

설명

Project-level QA를 QAMESH evidence와 feedback bundle로 연결합니다. 이 스킬은 auto qa namespace의 thin routing guidance이며, 실제 결과는 CLI 실행으로만 확인합니다.

Runner Boundary

QAMESH is the default project QA orchestration layer.
Playwright is not a competing QA mode. When detected, it becomes a browser/gui Journey runner adapter under QAMESH.
Ask users to choose the project under test, execution authority, environment/origin, credentials boundary, mobile/cloud device boundary, or explicit canary command. Do not ask them to choose between QAMESH and Playwright.

Boundary With Canary

auto qa는 deterministic user journey, evidence manifest, redaction, run index, release lane aggregation, and repair feedback를 다루는 QAMESH QA mesh입니다.
빠른 post-deploy smoke/status 확인만 필요하면 auto canary를 사용합니다. auto canary의 책임은 최신 운영 건강 상태를 판정하는 것이며, QAMESH evidence/feedback bundle을 만들지 않습니다.
auto qa release의 canary-explicit lane은 명시적 post-deploy smoke Journey Pack을 release gate 안에서 참조하는 bridge lane입니다. explicit Journey Pack이 없으면 setup gap으로 보고하고, canary command를 임의로 만들어 실행하지 않습니다.

사용법

/auto qa full --format json
/auto qa full --bootstrap --format json
/auto qa full --run --format json
/auto qa coverage --format json
/auto qa report --format json
/auto qa report --no-write --format json
/auto qa report --embed-media --format json
/auto qa profile check --format json
/auto qa plan --format json
/auto qa init --format json
/auto qa init --local-only --format json
/auto qa scenario init --format json
/auto qa scenario compile --format json
/auto qa scenario compile --dry-run --format json
/auto qa run --format json
/auto qa explore --dry-run --format json
/auto qa release --dry-run --format json
/auto qa release --roadmap --format json
/auto qa evidence --input <manifest> --output <dir> --surface browser --lane golden --scenario <id> --format json
/auto qa feedback --to codex --evidence <manifest> --format json

Read the full file on GitHub · 107 lines

Changes

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.

5d ago Changed · +31 lines · -4 tokens per session 13199c11e66f
9d ago First seen · 76 lines · 26 tokens per session scan A 0c1d5d51a6ee

Subscribe to this mod's changes

auto-qa is a skill published in the GitHub repository Insajin/autopus-adk (111 stars, last pushed yesterday), licensed MIT. It adds 22 tokens to every session and 2,862 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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