原始内容
🚀 Casely — AI QA Test Case Generator

Turn messy PDF requirements into TestRail-ready test cases in 8 minutes.
Free, open-source AI skill for Claude Code, Cursor, and any AI IDE.
The problem every QA engineer knows
You were hired to find bugs. Instead, you spend 40% of your week writing test cases.
Requirements scattered across 10 PDF files. Every project has different column names — manual reformatting every time. A single module takes 2 days to document. Then the TestRail import fails because the headers don't match.
❌ Requirements buried in PDF/DOCX/XLSX files with no structure
❌ Each project reinvents column names — manual mapping every sprint
❌ 50 test cases = 2–3 business days of repetitive writing
❌ TestRail import breaks due to column mismatches
❌ No coverage plan = missed edge cases and bugs reaching production
Every hour writing test cases is an hour not spent testing.
What Casely does
Casely is your Virtual QA Lead. It reads your requirements, learns your team's exact format, and writes the test cases — atomic, structured, and import-ready.
Requirements PDF → /parse → /style → /plan → /generate → /export → TestRail ✅
| Step | Command | What happens |
|---|---|---|
| Extract | /parse |
Docling OCR pulls tables and text from any PDF/DOCX |
| Learn | /style |
Casely reads your existing Excel and clones your column structure |
| Plan | /plan |
Generates a coverage map: "47 tests across 6 modules" |
| Write | /generate |
Creates atomic .md test cases — one file per test |
| Deliver | /export |
Batch-converts everything to TestRail-ready Excel |
Open exports/functional_TC001_happy_path.xlsx — it's a 1:1 match to your team's template, ready for immediate import.
Why QA teams switch to Casely
| Casely | Manual writing | Traditional tools | |
|---|---|---|---|
| Parses any format (PDF/DOCX/XLSX) | ✅ | ❌ | ❌ |
| Matches your column structure | ✅ | ❌ | ❌ |
| Generates a test plan automatically | ✅ | ❌ | ❌ |
| 1 test case = 1 file (atomic, reviewable) | ✅ | ❌ | ⚠️ bulk only |
| TestRail / Qase ready out of the box | ✅ | ❌ | ⚠️ manual fix |
| Works with English and Russian docs | ✅ | ❌ | ❌ |
| Free, runs locally, no cloud lock-in | ✅ | ✅ | ❌ |
⚡ Quick Start
Prerequisites: Python 3.10+ and uv
Option A — Skills CLI (recommended)
# with bunx
bunx skills add JohnWayneeee/casely-qa-skill
# or npx
npx skills@latest add JohnWayneeee/casely-qa-skill
Option B — Clone & run
git clone https://github.com/JohnWayneeee/casely-qa-skill.git
cd casely-qa-skill
uv sync
Drop your files into the project folder and run the workflow:
/init my-project
/parse
/style
/plan
/generate functional AccountTransfer
/export
8-minute walkthrough
Step 1 — Initialize
/init my-project
Drop two files into projects/my-project/input/:
requirements.pdf— your specification documentexample.xlsx— an existing test case file your team already uses
Casely learns your column structure from the example. No config needed.
Step 2 — Parse & plan
/parse # extracts text and tables from your PDF via Docling OCR
/style # reads your example.xlsx and clones the column structure exactly
/plan # output: "Detected 6 modules. Recommended: 47 test cases."
You now have a full coverage strategy before writing a single test case.
Step 3 — Generate
/generate functional AccountTransfer
Casely writes 10+ atomic .md files — one per test case. Review and edit in any text editor or Git UI before exporting.
Step 4 — Export
/export
Every .md file becomes a separate Excel file matching your team's template exactly. Import into TestRail, Qase, or any TMS — no manual reformatting.
Command reference
| Command | Action | Notes |
|---|---|---|
/init [name] |
Scaffold project workspace | Run once per project |
/parse |
Extract from PDF/DOCX | High-fidelity OCR via Docling |
/style |
Clone your Excel column format | Reads your example — zero config |
/plan |
Build ISTQB-aligned coverage map | Shows module breakdown and estimates |
/generate [type] |
Write atomic test cases | Produces one .md per test |
/export |
Convert all .md to Excel |
Batch output, import-ready |
Supported generation types: functional, negative, integration, boundary, smoke, security
Under the hood
- Docling Engine — advanced OCR and table extraction for complex, multi-column PDFs including scanned documents
- Atomic design — 1 test case = 1 source file = 1 Excel; no monolithic spreadsheets to untangle
- Style Guide System — no hardcoded columns; Casely learns from your existing files and replicates the exact structure
- Language agnostic — generates test cases in English or Russian, matching the language of your documents
Project structure
casely-qa-skill/
├── skill/casely/
│ ├── SKILL.md # AI skill definition and full workflow
│ ├── scripts/
│ │ ├── casely_parser.py # Document → Markdown converter (Docling)
│ │ └── export_to_xlsx.py # Markdown → Excel exporter
│ ├── references/ # Technical reference docs
│ └── evals/ # Evaluation test cases
├── docs/
│ └── hosted-web-version.md # Hosted version details
├── assets/ # Images and branding
├── pyproject.toml # Python dependencies
└── marketplace.json # Skill marketplace metadata
Hosted version for teams
This open-source skill runs locally in your AI IDE.
If you want a browser UI, file uploads, team review flow, and zero local setup:
casely.digital — join the early access list
The hosted version is built for QA teams that want to turn requirements into review-ready test cases without writing code or running local scripts.
Learn more about the hosted version →
FAQ
Does it work with scanned PDFs?
Yes. Casely uses Docling's OCR pipeline, which handles scanned documents, embedded tables, and mixed-format pages.
Can I use my own Excel column structure?
That's the core feature. Drop your existing template into input/ and run /style. Casely reads your column names and replicates them exactly — no configuration file needed.
Does it support Russian-language requirements?
Yes. The parser and generator work with English and Russian documents. Column names in your Excel template are preserved as-is.
Which test management systems are supported for import?
Any TMS that accepts Excel import: TestRail, Qase, Zephyr, Xray, and plain Excel. Because Casely replicates your own column structure, the output matches whatever format your team already uses.
What's the difference between the skill and the hosted version?
The skill runs locally inside your AI IDE (Claude Code, Cursor, etc.) — full control, no cloud, free forever.
The hosted version at casely.digital adds a browser UI, team review workflows, and cloud storage — no local setup required.
Contributing
Contributions are welcome. Please read CONTRIBUTING.md before opening a pull request.
- 🐛 Found a bug? Open an issue
- 💡 Have an idea? Request a feature
- ⭐ Did it help? Star the repo — it helps other QA engineers find this tool
⭐ Star History
If Casely saved you a work week, a star helps others find it.
License
MIT — free to use, modify, and distribute.
Made for QA engineers who were hired to find bugs, not write documents.
casely.digital — the hosted version for teams