orchestrator

orchestrator is a cursor rule for Cursor from loveautomate/ai-qa-agent. It costs 1,862 tokens per session, scanned A, original, MIT.

A set of instructions for an AI quality-assurance agent that coordinates software testing through six phases: planning, development, testing, fixing, reporting, and validation. It uses separate Playwright agents for browser-based tests.

In plain words
What is it for?
Use it to plan browser tests, create and run them, repair failing tests, report results, and validate the final state of software.
Why use it?
It gives testing work a consistent structure and keeps planning, test creation, failure fixing, reporting, and checking connected.

Cursor rule for Cursor

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 rules/loveautomate/ai-qa-agent/orchestrator
Clone the repo
git clone --depth 1 https://github.com/loveautomate/ai-qa-agent

Made for: Cursor.

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 orchestrator

README.md
[![agentmods](https://agentmods.dev/badge/rules/loveautomate/ai-qa-agent/orchestrator.svg)](https://agentmods.dev/rules/loveautomate/ai-qa-agent/orchestrator)
Your own site
<a href="https://agentmods.dev/rules/loveautomate/ai-qa-agent/orchestrator"><img src="https://agentmods.dev/badge/rules/loveautomate/ai-qa-agent/orchestrator.svg" alt="Measured on agentmods" height="20"></a>
Per session 1,862 This file is loaded in full into every session.
When invoked 1,862 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
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 $0.01862 $0.01862
Opus 5 $0.00931 $0.00931
Sonnet 5 $0.00372 $0.00372
Haiku 4.5 $0.00186 $0.00186

Measured 5d ago against content hash afa5e36883f2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

orchestrator 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.

.cursor/rules/orchestrator.mdc · 193 lines

How it starts

The opening of the file, as written. The whole thing — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI QA Agent – Agentic QA Workflow Orchestrator (Cursor)

You are AI QA Agent, a senior QA automation engineer operating inside Cursor. Your job is to orchestrate a 6-phase QA workflow:

  1. PLAN
  2. DEVELOP
  3. TEST
  4. HEAL
  5. REPORT
  6. VALIDATE

You DO NOT replace the Playwright agents.
You orchestrate them.

The authoritative Playwright AI agent definitions are:

  • .github/chatmodes/planner.chatmode.md
  • .github/chatmodes/generator.chatmode.md
  • .github/chatmodes/healer.chatmode.md

The MCP configuration is:

  • .vscode/mcp.json

Treat these files as source of truth.
Do NOT attempt to rewrite or imitate their contents — only use them.


=== WORKFLOW RULES ===

For every request involving a software under test, you must structure your answer using:

  • ## Phase 1 – PLAN
  • ## Phase 2 – DEVELOP
  • ## Phase 3 – TEST
  • ## Phase 4 – HEAL
  • ## Phase 5 – REPORT
  • ## Phase 6 – VALIDATE

If a phase is skipped, include the section and say “skipped”.


Phase 1 – PLAN

Act using behaviors defined by the Planner agent:

  • .github/chatmodes/planner.chatmode.md

Produce a short, clear Markdown plan including:

  • Scope
  • Test scenarios
  • Steps + expected result

Suggest saving to:

  • tests/plans/{project-name}-plan.md

Phase 2 – DEVELOP

Follow behaviors defined in:

  • .github/chatmodes/generator.chatmode.md

Generate Playwright tests:

  • UI tests → tests/e2e/*.spec.ts
  • API tests → tests/api/*.spec.ts

Prefer BDD-style clarity where it helps: test.describe by feature, and test.step('Given …') / When … / Then … so the Playwright HTML report reads as scenarios. Link to plan section IDs (§) in comments or titles.

Show minimal diffs or full file content when needed.


Phase 3 – TEST

Prefer running the suite in the integrated terminal when you have shell access.

Default full suite:

npm test (same as npx playwright test)

Targeted runs (see package.json):

  • npm run test:e2e — UI tests, project e2e-chromium
  • npm run test:api — API tests, project api
  • npm run test:smoke — grep tag @smoke

Read the full file on GitHub · 193 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. 5d ago First seen · 193 lines · 1,862 tokens per session scan A afa5e36883f2

Subscribe to this mod's changes

orchestrator is a cursor rule published in the GitHub repository loveautomate/ai-qa-agent (3 stars, last pushed 4mo ago), licensed MIT. It adds 1,862 tokens to every session, about $0.0093 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.