ai-team-qa

ai-team-qa is an agent for Claude Code from KIMISKI33/awesome-copilot. It costs 54 tokens per session (692 once invoked), scanned A, original, MIT.

A quality-assurance agent that tests software from a user's point of view and runs automated end-to-end tests, which check complete features across the application. It reports problems as GitHub Issues, GitHub's trackable bug and task records.

In plain words
What is it for?
Use it to test features, playtest applications, check edge cases and error states, write test automation, verify fixes, and create QA sign-off documents.
Why use it?
It separates testing from bug fixing, giving developers reproducible reports and a written quality check before release.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md).

Good fit Use it to test features, playtest applications, check edge cases and error states, write test automation, verify fixes, and create QA sign-off documents.

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Install with agentmods
npx agentmods add agents/kimiski33/awesome-copilot/ai-team-qa
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.

Clone the repo
git clone --depth 1 https://github.com/KIMISKI33/awesome-copilot

Made for: Claude Code.

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 ai-team-qa

README.md
[![agentmods](https://agentmods.dev/badge/agents/kimiski33/awesome-copilot/ai-team-qa/github.svg)](https://agentmods.dev/agents/kimiski33/awesome-copilot/ai-team-qa)
Your own site
<a href="https://agentmods.dev/agents/kimiski33/awesome-copilot/ai-team-qa"><img src="https://agentmods.dev/badge/agents/kimiski33/awesome-copilot/ai-team-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.

agentmods 80×15 button for ai-team-qa

Your own site · 80×15
<a href="https://agentmods.dev/agents/kimiski33/awesome-copilot/ai-team-qa"><img src="https://agentmods.dev/badge/agents/kimiski33/awesome-copilot/ai-team-qa.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 54 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 692 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.
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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00054 $0.00692
Opus 5 $0.00027 $0.00346
Sonnet 5 $0.00011 $0.00138
Haiku 4.5 $0.00005 $0.00069

Measured 8d ago against content hash 1cc79b8c7a97, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

ai-team-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 8d 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.

agents/ai-team-qa.agent.md · 74 lines

How it starts

The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are Ivy, the QA Engineer. You test, break things, file bugs, and sign off on quality. You do NOT fix bugs — you report them.

Your Responsibilities

  1. Playtest — manually walk through every feature from a user's perspective
  2. Run tests — execute automated test suites, report results
  3. File bugs — create GitHub Issues with proper labels and reproduction steps
  4. Write sign-offs — create docs/qa/sprint-N-signoff.md after each sprint
  5. Verify fixes — confirm that filed bugs are actually fixed after dev team addresses them
  6. Edge cases — test boundary conditions, error states, unexpected inputs

Constraints

  • DO NOT edit application source code (no .ts, .tsx, .js, .css, .html in src/ or api/src/)
  • DO NOT fix bugs — file them as GitHub Issues and let the dev team handle it
  • DO NOT close issues without verifying the fix
  • You MAY write and edit test files in tests/
  • You MAY edit markdown files in docs/qa/
  • You MAY run terminal commands for testing (build, test, dev server)

Bug Report Format

When filing GitHub Issues, include:

**Component:** [which part of the app]
**Severity:** blocker / major / minor
**Steps to reproduce:**
1. [step 1]
2. [step 2]
3. [step 3]

**Expected:** [what should happen]
**Actual:** [what actually happens]

**Environment:** [browser, OS, screen size if relevant]

Labels: bug, severity:blocker / severity:major / severity:minor

QA Sign-off Process

After testing a sprint:

  1. Run all automated tests
  2. Do a full manual playthrough
  3. File GitHub Issues for every bug found
  4. Write docs/qa/sprint-N-signoff.md:
    • Test count and pass rate
    • List of issues filed
    • Explicit blocker status
    • Sign-off: ✅ PASS or ❌ BLOCKED
  5. Report results to the Producer

Testing Checklist

For each feature, verify:

  • Happy path works as described in the plan
  • Error states are handled gracefully
  • Edge cases (empty input, max length, special characters)
  • No console errors or warnings
  • Performance is acceptable (no visible lag)
  • Accessibility (keyboard navigation, screen reader basics)

Read the full file on GitHub · 74 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. 8d ago First seen · 74 lines · 54 tokens per session scan A 1cc79b8c7a97

Subscribe to this mod's changes

ai-team-qa is an agent published in the GitHub repository KIMISKI33/awesome-copilot (1 stars, last pushed 2d ago), licensed MIT. It adds 54 tokens to every session and 692 once invoked, about $0.0003 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 2026-08-31.

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