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QA Copilot

An agent-built QA auditor - give it a spec and a URL, and it browser-tests your app against every requirement, then scores release readiness.

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About this project

QA Copilot is an AI QA audit tool built end-to-end by the agent factory. It validates whether a deployed application actually matches its feature specification: you provide a spec - selected from Mindlap, pasted, or uploaded as PDF, DOCX, or Markdown - plus a staging URL, and it extracts structured requirements and acceptance criteria for you to review and approve. From those it generates happy-path, negative, boundary, and edge-case scenarios, executes them with browser automation, and maps every result back to a requirement as passed or failed while capturing screenshots, video, and traces as evidence. The output is a complete QA audit report - audit score, requirement coverage, defects by severity, risk analysis, and a clear release recommendation - with every run saved to history, so teams can tell whether a feature is ready to ship without writing manual test cases or depending on dedicated QA.

Demo

At a glance

2.8h

Agent hours

19M

Tokens

1

Laps

11

Stories

19M

tokens

Others · 100%

Tokens by stage

Implement

15M

Merge

1M

patch-merge

1M

re-implement+pr

2M

Pipeline

Stage

Runs

Tokens

Duration

Implement

11

15M

1.3h

Merge

4

1M

0.2h

patch-merge

3

1M

0.1h

re-implement+pr

1

2M

0.1h

Engines used

Others

Tokens

16M

Runs

22

Agent hours

2.8h

Success

95.5%

Agent team

developer

21 runs · 2.8h

21 passed · 0 failed

Artifacts

PRD

markdown

QA Copilot - Product Requirements Document

Spec-driven QA audit

1. Overview

QA Copilot is an AI-powered QA audit plugin that validates whether a deployed application matches its feature specification.

Users can provide specifications from Mindlap, paste specifications directly, or upload specification documents. The engine analyzes requirements, generates validation scenarios, executes browser-based testing, and produces a comprehensive QA audit report.

The goal is to help product managers, founders, and engineering teams quickly determine whether a feature is ready for release without manually creating test cases or performing repetitive QA validation.

2. Problem Statement

Most software teams validate features manually after development is complete. This process is often time-consuming, inconsistent, dependent on QA resources, and difficult to scale.

Teams frequently face challenges such as:

  • Acceptance criteria being missed
  • Incomplete test coverage
  • Manual test case creation
  • Lack of visibility into release readiness
  • Bugs discovered late in the release cycle

As a result, features are shipped with defects, product managers manually validate requirements, QA becomes a bottleneck, and teams lack confidence in releases.

QA Copilot automates specification-based validation and provides objective release-readiness reporting.

3. Goals (MVP)

  • Accept feature specifications from multiple sources
  • Extract requirements and acceptance criteria
  • Generate validation scenarios automatically
  • Execute browser-based testing
  • Validate implementation against requirements
  • Detect defects and workflow failures
  • Generate QA audit reports
  • Provide release-readiness scoring
  • Store audit history

4. Non-Goals

The MVP will not: create or manage bug tickets, modify application code, perform load testing, perform security testing, perform API testing, support native mobile applications, support desktop applications, provide production monitoring, or support cross-browser testing.

5. Target Users

  • Product Manager - validates delivered features against specifications; needs confidence that acceptance criteria are implemented correctly.
  • Engineering Manager - responsible for release quality and deployment readiness; needs visibility into risks before approving releases.
  • Founder - needs a fast way to validate customer-facing functionality without depending on dedicated QA resources.

6. Inputs

6.1 Specification Source

Users can provide a specification using one of the following methods.

  • Mindlap Specification - select an existing feature specification stored in Mindlap.
  • Paste Specification - paste PRDs, feature specifications, user stories, acceptance criteria, Jira tickets, or Notion documents directly into the plugin.
  • Upload Specification - supported formats: PDF, DOCX, Markdown, TXT.

The system automatically extracts requirements, acceptance criteria, user stories, and functional requirements.

6.2 Application URL

Required: a staging, QA environment, or production URL.

Optional: login credentials, test account credentials, and additional testing instructions (e.g. "Use admin account", "Start testing from onboarding flow").

7. User Flow

  1. Provide Specification - select a Mindlap spec, paste a specification, or upload a document.
  2. Provide Application URL - enter the target URL, optional credentials, and optional instructions.
  3. Requirement Extraction - convert unstructured specifications into structured requirements, acceptance criteria, business rules, and validation targets. Users can review and edit extracted requirements before execution.
  4. Generate Validation Plan - happy path, negative, boundary, edge case, and exploratory scenarios.
  5. Execute Validation - browser automation executes scenarios against the application.
  6. Analyze Results - evaluate requirement compliance, workflow completion, UI behavior, and error handling.
  7. Generate QA Audit Report - audit score, requirement coverage, defects detected, risk analysis, and release recommendation.

8. Core Features

Feature 1: Specification Ingestion

Accept specifications from Mindlap documents, pasted text, PDF, DOCX, Markdown, and text files. The system normalizes all inputs into a common requirement model, outputting requirements, user stories, acceptance criteria, and business rules.

Feature 2: Requirement Review

Before execution, users review AI-extracted requirements and can edit, delete, or add requirements. Only approved requirements are used for validation.

Feature 3: Requirement Extraction Engine

Extract structured requirements from specifications.

IDRequirement
REQ-01Admin can invite users
REQ-02Invitation email is sent
REQ-03Admin can revoke invitations
REQ-04Duplicate invitations are prevented

Feature 4: Validation Scenario Generator

Convert requirements into executable scenarios: happy path, invalid input, edge case, user workflow, and exploratory. For "Admin can invite users", generated tests include invite valid user, invite invalid email, invite duplicate user, invite suspended user.

Feature 5: Browser Validation Engine

Execute scenarios against the target application using browser automation.

  • Capabilities: form interactions, navigation flows, authentication flows, CRUD operations, multi-step workflows, user journey validation.
  • Captured artifacts: screenshots, videos, browser logs, network requests, DOM snapshots, execution traces.
  • Execution status: pending, running, completed, failed.

Feature 6: Requirement Validation Engine

Map execution results back to requirements. Requirement status: passed, failed, partially validated, not tested.

Feature 7: Defect Detection

For each defect, generate a title, severity, description, expected behavior, actual behavior, reproduction steps, and supporting evidence. Severity levels: critical, high, medium, low.

Feature 8: Risk Analysis

Identify risks beyond direct failures - missing validation, weak error handling, broken user journeys, unverified functionality. Risk categories: functional risk, user experience risk, reliability risk.

Feature 9: QA Audit Report

A structured report with:

  • Executive Summary - audit score, requirements passed/failed, critical defects, release recommendation.
  • Acceptance Criteria Coverage - total, covered, failed, untested criteria.
  • Defect Summary - defects by severity, screenshots, supporting evidence.
  • Risk Summary - high-risk areas and recommendations.
  • Suggested Additional Testing - untested workflows and recommended validations.

Feature 10: Audit History

Store previous audit runs so users can compare audit scores, defects discovered, defects resolved, and coverage changes.

9. Dashboard Screens

  1. Audit Configuration - specification source, URL input, credentials, Run Audit button.
  2. Requirement Review - extracted requirements, acceptance criteria, edit and approve controls.
  3. Audit Execution - current progress, running validations, screenshots, execution logs.
  4. Audit Report - audit score, requirement coverage, defects, risks, release recommendation.
  5. Audit History - previous audits, audit scores, defect counts, execution timestamps.

10. Success Metrics

  • Product: audits executed, requirements validated, audit reports generated, defects detected.
  • Customer: time saved vs manual QA, reduction in QA effort, acceptance criteria coverage, defects found before release, release confidence improvement.

11. Future Roadmap

  • Phase 2: scheduled audits, GitHub integration, pull request validation, regression testing, email reports.
  • Phase 3: API testing, cross-browser testing, mobile application testing, release readiness trends, continuous deployment validation.

12. MVP Demo Scenario

A user provides a feature specification by selecting a Mindlap document, pasting a specification, or uploading a PRD, enters a staging URL, and clicks Run Audit. QA Copilot extracts requirements, generates validation scenarios, and executes browser-based testing against the application.

The system discovers 2 failed acceptance criteria, 1 critical defect, and 3 medium-severity issues. The final report shows an Audit Score of 82/100, Coverage of 95%, and a Release Status of Not Ready.

QA Copilot delivers a complete QA audit within minutes, helping teams understand whether a feature matches its specification and is ready to ship.

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