qa

qa is a skill for Claude Code, Codex from karlarao/afk. It costs 58 tokens per session (1,063 once invoked), scanned A, a copy of qa, MIT.

An interactive quality-assurance session in which a user describes a problem and the agent clarifies it, investigates the codebase, and files a GitHub issue. Quality assurance, or QA, is the process of checking that software behaves as expected.

In plain words
What is it for?
Use it to report bugs, describe unexpected behavior, clarify reproduction steps, decide whether problems belong in one issue or several, and create GitHub issues.
Why use it?
It turns an informal bug report into a durable, user-focused issue with enough context to act on. It also uses the codebase's own terminology while keeping internal implementation details out of the issue.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/karlarao/afk/qa
Any agent
npx skills add karlarao/afk --skill qa
Clone the repo
git clone --depth 1 https://github.com/karlarao/afk

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.

agentmods badge for qa

README.md
[![agentmods](https://agentmods.dev/badge/skills/karlarao/afk/qa.svg)](https://agentmods.dev/skills/karlarao/afk/qa)
Your own site
<a href="https://agentmods.dev/skills/karlarao/afk/qa"><img src="https://agentmods.dev/badge/skills/karlarao/afk/qa.svg" alt="Measured on agentmods" height="20"></a>
Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,063 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod 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.

ModelPer sessionOnce invoked
Fable 5 $0.00058 $0.01063
Opus 5 $0.00029 $0.00531
Sonnet 5 $0.00012 $0.00213
Haiku 4.5 $0.00006 $0.00106

Measured 4d ago against content hash d9727aac6503, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

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 4d 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.

Origin

This is a copy

100% identical to qa — 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.

skills/matt-cohort3/qa/SKILL.md · 131 lines

How it starts

The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.

QA Session

Run an interactive QA session. The user describes problems they're encountering. You clarify, explore the codebase for context, and file GitHub issues that are durable, user-focused, and use the project's domain language.

For each issue the user raises

1. Listen and lightly clarify

Let the user describe the problem in their own words. Ask at most 2-3 short clarifying questions focused on:

  • What they expected vs what actually happened
  • Steps to reproduce (if not obvious)
  • Whether it's consistent or intermittent

Do NOT over-interview. If the description is clear enough to file, move on.

2. Explore the codebase in the background

While talking to the user, kick off an Agent (subagent_type=Explore) in the background to understand the relevant area. The goal is NOT to find a fix — it's to:

  • Learn the domain language used in that area (check UBIQUITOUS_LANGUAGE.md)
  • Understand what the feature is supposed to do
  • Identify the user-facing behavior boundary

This context helps you write a better issue — but the issue itself should NOT reference specific files, line numbers, or internal implementation details.

3. Assess scope: single issue or breakdown?

Before filing, decide whether this is a single issue or needs to be broken down into multiple issues.

Break down when:

  • The fix spans multiple independent areas (e.g. "the form validation is wrong AND the success message is missing AND the redirect is broken")
  • There are clearly separable concerns that different people could work on in parallel
  • The user describes something that has multiple distinct failure modes or symptoms

Keep as a single issue when:

  • It's one behavior that's wrong in one place
  • The symptoms are all caused by the same root behavior

4. File the GitHub issue(s)

Create issues with gh issue create. Do NOT ask the user to review first — just file and share URLs.

Issues must be durable — they should still make sense after major refactors. Write from the user's perspective.

Read the full file on GitHub · 131 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.

  1. 4d ago First seen · 131 lines · 58 tokens per session scan A d9727aac6503

Subscribe to this mod's changes

qa is a skill published in the GitHub repository karlarao/afk (2 stars, last pushed 3mo ago), licensed MIT. It adds 58 tokens to every session and 1,063 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to qa, differing in 0 lines, and is treated as a copy.

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