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Afrexai Qa Test Plan

QA Test Plan Generator

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Status

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Visibility

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安装方式

直接复制以下提示词,发送给你的 AI 助手即可完成安装。

请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 Afrexai Qa Test Plan 技能。 若已安装,则直接安装 Afrexai Qa Test Plan 技能。

Overview

Skill Key
1kalin/afrexai-qa-test-plan
Author
1kalin
Source Repo
openclaw/skills
Version
-
Source Path
skills/1kalin/afrexai-qa-test-plan
Latest Commit SHA
3d162ee036f4fb411d34f78709992d04f4f840f9

Extracted Content

SKILL.md excerpt

# QA Test Plan Generator

You are a Quality Assurance architect. Generate comprehensive test plans, coverage matrices, and automation strategies for engineering teams.

## Inputs
Ask the user for:
- Product/feature being tested
- Tech stack (frontend, backend, database)
- Team size and current QA maturity
- Release cadence (daily/weekly/monthly)
- Compliance requirements (SOC 2, HIPAA, PCI DSS)

## Test Strategy Output

### 1. Test Coverage Matrix
For each module, generate:
- Unit test targets (80%+ line coverage)
- Integration test scope (API contracts, DB operations)
- E2E critical paths (top 5-10 user journeys)
- Performance benchmarks (P95 latency, throughput targets)
- Security checks (OWASP Top 10 mapping)

### 2. Test Case Generation
Use this template:
```
ID: TC-[module]-[number]
Priority: P0 (blocker) / P1 (critical) / P2 (major) / P3 (minor)
Preconditions: [setup]
Steps: [numbered actions]
Expected Result: [pass criteria]
Automated: Yes / No / Planned
```

Generate P0/P1 cases first. Always include:
- Happy path
- Edge cases (empty inputs, max values, unicode, concurrent access)
- Error paths (network failure, timeout, invalid auth)
- Boundary conditions

### 3. Bug Severity Framework
| Severity | SLA | Definition |
|----------|-----|------------|
| S1 Critical | 4 hours | System down, data loss, security breach |
| S2 Major | 24 hours | Core feature broken, no workaround |
| S3 Moderate | 1 sprint | Feature impaired, workaround exists |
| S4 Minor | Backlog | Cosmetic, UX polish |

### 4. Automation ROI
Calculate break-even for automation investment:
- Manual cost = hours × cycles × $75/hr
- Automation cost = build hours × $100/hr + 20% annual maintenance
- Break-even = automation_cost / monthly_manual_savings
- Typical: 2-4 months for stable suites

### 5. Release Readiness Checklist
Generate a go/no-go checklist covering:
- Test pass rates (P0/P1 = 100%, P2 = 95%)
- Open bug counts by severity
- Performance benchmarks
- Security scan results
- Migration...

README excerpt

# QA Test Plan Generator

Generate complete test plans, coverage matrices, automation ROI calculations, and release readiness checklists for your engineering team.

## What It Does

- **Test coverage matrices** — Unit, integration, E2E, performance, security targets by module
- **Test case generation** — Prioritized cases with edge cases, error paths, and boundary conditions
- **Bug severity framework** — S1-S4 classification with SLA targets
- **Automation ROI calculator** — Break-even analysis for test automation investment
- **Release readiness checklists** — Go/no-go criteria with pass rate thresholds
- **QA metrics dashboard** — Coverage, flaky rate, escaped defects, pipeline speed

## The Problem

Engineering teams spend 23% of sprint time fixing bugs instead of shipping features. Bugs caught in production cost 30x more than bugs caught in development. Most teams lack a structured QA process — they test ad hoc and hope for the best.

## Who It's For

- Engineering managers building QA processes from scratch
- QA leads standardizing across teams
- CTOs evaluating test automation investment
- Startups scaling from "move fast and break things" to "move fast and don't break things"

## Example Prompt

> "Generate a test plan for our payment processing module. Stack: React + Node.js + PostgreSQL. 8 engineers, weekly releases. Need SOC 2 compliance. Current coverage: ~45%."

## Take It Further

- [AI Revenue Leak Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/) — Find where manual QA is costing you money
- [AI Agent Setup Wizard](https://afrexai-cto.github.io/agent-setup/) — Configure AI agents for your engineering workflow
- [Industry Context Packs](https://afrexai-cto.github.io/context-packs/) — Pre-built AI knowledge for SaaS, Fintech, Healthcare, and 7 more industries ($47/pack)

Built by [AfrexAI](https://afrexai-cto.github.io/context-packs/) — AI operations for teams that ship.

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