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johnwayneeee

Casely

by JohnWayneeee · GitHub ↗ · v0.1.0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install casely
Description
Intelligent QA assistant that automates writing test cases from project documentation. Use when the user wants to generate test cases from requirements, runs...
README (SKILL.md)

Casely — QA Test Case Generator

Casely automates the most time-consuming part of a QA engineer's job: writing test cases. It reads requirement documents and learns from your team's existing test case examples to produce structured, style-consistent test suites ready for import into any Test Management System.

Why this matters

Manual test case writing accounts for ~40% of a QA engineer's time. Requirements come in fragmented formats (PDF, DOCX, XLSX). Every team has its own column structure, naming conventions, and writing style. Casely solves this by:

  • Converting any document format to clean Markdown via docling.
  • Extracting formal style rules from your team's example test cases.
  • Generating test cases that match your team's exact structure and tone.
  • Exporting to Excel with correct column mapping for TMS import.

Commands

/init [ProjectName]

Creates a new isolated project workspace and verifies the environment.

/parse

Runs the CaselyParser to convert all raw assets (requirements and examples) to Markdown.

/style

Analyzes example test cases and generates a persistent test_style_guide.md.

/plan

Scans parsed requirements and suggests a testing plan with modules and test types.

/generate [type]

Generates atomic test cases of the specified type (functional, negative, integration, boundary, etc.).

/export

Converts generated Markdown test cases into a formatted .xlsx file.


Full Workflow

Phase 1: Project Initialization & Environment Setup (/init)

When the user runs /init [ProjectName] (or asks to start a new testing project):

  1. Create Directories: Create the project directory structure under projects/ in the repository root:

    • input/requirements/
    • input/examples/
    • processed/requirements/
    • processed/examples/
    • results/
    • exports/
  2. Environment Setup via uv:

    • Location: Dependencies are defined in pyproject.toml at the repository root (not inside the skill folder). Scripts expect uv sync to have been run from that root.
    • Check if pyproject.toml exists at the repo root. If not, run uv init there.
    • Install/verify dependencies: uv add docling openpyxl (or uv sync from repo root).
    • This ensures a lightning-fast setup and handles all sub-dependencies (e.g. torch for docling) automatically.
  3. Confirm to the user:

    • "Project {project_name} initialized via UV. Environment and dependencies (docling, openpyxl) are ready."
    • "Place your requirement documents into projects/{project_name}/input/requirements/ and examples into projects/{project_name}/input/examples/."

Phase 2: Document Parsing (/parse)

When the user runs /parse (or asks to parse/process documents):

  1. Locate the project. If there's only one project under projects/, use it automatically. If multiple exist, ask the user which one.

  2. Run CaselyParser — The parser is located at scripts/casely_parser.py within this skill. It uses docling and supports all major formats.

    Via CLI (optional arguments, auto-detects latest project if omitted):

    uv run python \x3Cskill-path>/scripts/casely_parser.py
    

    (Or manual path if needed)

    uv run python \x3Cskill-path>/scripts/casely_parser.py "projects/{name}/input/requirements" "projects/{name}/processed/requirements"
    
  3. Report results to the user: how many files were parsed, any errors, and summary of processed files.

Phase 3: Style Guide Creation (/style)

  1. Read all parsed example files from processed/examples/.

  2. Analyze the table structure to extract headers, data types, and mandatory fields.

    • CRITICAL: The style guide MUST be an exact replica of the example's column structure.
    • MANDATORY: Transfer ALL headers from the example files to the test_style_guide.md in their exact order. Do not rename, omit (e.g., "Comments", "Author"), or add new columns unless explicitly requested.
  3. Analyze the writing style to extract language, tone, and formatting patterns (e.g., how steps are phrased).

  4. Generate test_style_guide.md in the project root. This file acts as the "source of truth" and must explicitly define the horizontal table row structure.

  5. Present the style guide to the user for review. Any manual adjustments to this file will be respected by the generator.

Phase 4: Professional Test Design & Planning (/plan)

  1. Load Context & Analysis:

    • Read parsed requirements from processed/requirements/.
    • Load test_style_guide.md to match example structure (columns → test complexity).
  2. Structural Breakdown:

    • Extract modules/endpoints/logic blocks from requirements.
    • Categorize by Level: API (fields/status), Integration (flows), E2E (scenarios).[web:8]
  3. Smart Estimation (Style-Driven):

    • Metrics from Style Guide: Fields per test (from columns), branches from logic.
    • Coverage Tiers (total cases based on examples):
      Tier Cases/Module Coverage Focus
      Smoke 1-3 Min Golden Path[web:13]
      Critical (80%) N (fields*0.8) Key paths High-risk (finance/auth)
      Full All perms 100% Edges/negatives
    • Risk Scoring: High (security), Med (logic), Low (UI).[web:8]
  4. Traceability & Prep:

    • Quick RTM Preview: Req ID → Planned Cases (e.g., "REQ-001 → 5 cases").
    • Data/Deps: Test data rules (valid/edge), mocks needed.
  5. Output Plan:

    • Table by Module: Module | Level | Est. Cases (80%) | Type | Tools.
    • MANDATORY: Provide ready-to-copy commands for each module.
    • Save test_plan.md (importable to TMS).
    • Ask: "Generate Critical Path? /generate functional MODULE_NAME" or "/generate negative MODULE_NAME".

Next: "/generate [type] will create exactly the estimated number of files, with each file containing one atomic test case matching your style guide."

Phase 5: Test Case Generation (/generate [type])

  1. Load context:

    • BIDING: Read test_style_guide.md (Mandatory Source of Truth).
    • Read relevant parsed requirement files.
    • Target specific module and test type.
  2. Generate ATOMIC test cases:

    • One File = One Test Case (1 ID = 1 Scenario): Each test case MUST be saved as a separate Markdown file in results/.
    • Horizontal Structure: Each file MUST contain exactly ONE horizontal table row (header row + data row). Do NOT use vertical "key-value" lists.
    • Naming Convention: {type}_{id}_{short_description}.md.
    • Match the style guide exactly — same columns (1:1 with example), same tone, same structure.
    • No Hallucinations — only use columns and data points supported by the guide and requirements.
  3. Proactive Report:

    • Notify the user of created files.
    • Mandatory Next Step: Always advise the user on what else they can generate. Example: "I've generated functional cases. You can now run /generate negative to check error handling or /generate security for device metadata."

Phase 6: Export to Excel (/export)

  1. Convert Markdown files to Excel using scripts/export_to_xlsx.py.
    • Smart Execution: The script automatically detects the most recently modified project in the projects/ directory if no paths are provided.
  2. Atomic One-to-One Export: For every .md file in results/, the tool creates exactly one corresponding .xlsx file in exports/.
    • Behavior: Direct format conversion preserving the file count.
    • Naming: Files are named identically to their source: {type}_{id}_{short_description}.xlsx.
  3. Internal Structure: Each Excel file contains a single sheet called "Test Case" with the columns exactly matching the project's style guide.
  4. Plain Text Export: Content is exported as plain text with support for multi-line cells (using \x3Cbr>).
  5. Save to exports/.

Important Guidelines

Proactive Guidance (Crucial)

After every command, Casely MUST provide a "Next Step" block.

  • After /init -> suggest /parse.
  • After /parse -> suggest /style.
  • After /style -> suggest /plan.
  • After /plan -> list specific commands like /generate functional or /generate negative.
  • After /generate -> suggest /export OR other generation types.

Language Awareness

Casely is language-agnostic for data. It will detect the language of the provided examples (e.g., Russian) and generate test cases in that same language. The internal logic and style guide should bridge this gap.

Atomic over Composite

Validators should always prefer multiple specialized test cases over one "all-in-one" case. This ensures clearer test results and easier bug localization.

Style Guide is King

The style guide is the single source of truth. Do not invent new columns or change formatting unless the style guide is updated first.


Skill Files

Scripts (scripts/)

  • scripts/casely_parser.py — Document-to-Markdown converter (Docling).
  • scripts/export_to_xlsx.py — Markdown-to-Excel exporter.

References (references/)

  • references/parser_usage.md — Technical details on calling the parser.
  • references/export_guide.md — Details on the MD-to-Excel conversion logic.
  • references/style_analysis_prompts.md — Methodologies for style extraction.
Usage Guidance
This skill appears to implement the described parser/exporter, but there are operational mismatches you should resolve before running: 1) The registry metadata lists no required binaries, yet the SKILL.md requires 'python' and a dependency manager called 'uv' and instructs installing docling/openpyxl at the repository root. Verify you have (or are willing to install) 'uv' and Python and understand what 'uv add' or 'uv sync' will change in your repo (pyproject.toml). 2) Because docling may pull heavy dependencies (e.g., torch or model downloads), run installs in an isolated virtual environment or sandbox to avoid impacting other projects. 3) Inspect scripts/scripts for any unwanted behavior (they are readable and do not show network calls), and confirm you are comfortable with the skill reading/writing under projects/ and creating test_style_guide.md files. 4) Ask the author for an explicit install spec (or provide one yourself) and clarification on 'uv' usage; require that dependency installs be done in a dedicated virtual environment. If you cannot verify those items, treat the skill as potentially risky and test it in an isolated environment first.
Capability Analysis
Type: OpenClaw Skill Name: casely Version: 0.1.0 The OpenClaw skill 'casely' is designed for QA test case generation, converting documents to Markdown and exporting to Excel. All file operations are confined to a dedicated 'projects/' directory structure. The `SKILL.md` instructions, while directive, focus on task execution and user guidance, without any evidence of prompt injection for malicious purposes. Dependency management via `uv` is standard, and the skill explicitly adds benign packages (`docling`, `openpyxl`). There is no indication of data exfiltration, unauthorized execution, persistence mechanisms, or obfuscation. The code aligns with the stated purpose and lacks any high-risk behaviors that suggest malicious intent.
Capability Assessment
Purpose & Capability
The name/description align with included scripts (a parser and an exporter) that convert documents to Markdown and XLSX test-case exports. However, the SKILL.md asks the operator to run 'uv' and to manage dependencies at the repository root (pyproject.toml), while the skill metadata declares no required binaries or install steps — that mismatch is unexpected. A legitimate implementation would normally declare required runtime binaries (e.g., python) or include an install spec if it needs to install heavy libraries like docling/torch.
Instruction Scope
Runtime instructions direct the agent/user to modify and depend on the repository root (check/create pyproject.toml, run 'uv init', 'uv add', 'uv sync'), create projects/ directories, and auto-detect the latest project by scanning projects/. That expands the skill's scope beyond its own folder and assumes permission to install/manage dependencies at repo root. The instructions also mandate copying all columns from example files verbatim into a persistent style file, which is business-logic but must be understood by users before automated runs. No instructions attempt to read unrelated secrets, but the repo-root dependency requirement and global install actions are scope creep relative to a small, self-contained skill.
Install Mechanism
There is no install spec in the registry entry (instruction-only), but the code requires third-party Python packages (docling, openpyxl). The SKILL.md tells the user to run 'uv add docling openpyxl' or 'uv sync' at the repository root to install dependencies. Relying on an out-of-band dependency manager (uv) without declaring it is risky: 'uv' is not a standard, universally-available tool and could change behavior. No remote download URLs or obscure hosts are used in the skill files themselves, and the included Python scripts are readable and contain no network exfiltration logic.
Credentials
The skill does not request environment variables, credentials, or config paths. Its filesystem access is limited to creating and reading project subdirectories (projects/, processed/, results/, exports/) and the repository root pyproject.toml. Those filesystem operations are consistent with a document-processing exporter, though users should note the expectation of reading/writing under the repository root.
Persistence & Privilege
The skill is not marked always:true and does not attempt to modify other skills or system-wide agent settings. It will create files in project folders and a persistent test_style_guide.md per project, which is expected for its functionality.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install casely
  3. After installation, invoke the skill by name or use /casely
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
Initial release of Casely – an intelligent QA assistant for automated test case generation. - Automates QA workflows: parses requirements (PDF/DOCX/XLSX), learns team-specific test style, generates atomic test cases, and exports to Excel for TestRail import. - Provides clear commands: `/init`, `/parse`, `/style`, `/plan`, `/generate`, `/export`. - Ensures exact adherence to your team’s test case structure and writing conventions. - Supports full workflow from environment setup and parsing to test planning and TMS-ready export. - Integrates tools like `docling` and `openpyxl` for seamless document handling and output.
Metadata
Slug casely
Version 0.1.0
License
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Casely?

Intelligent QA assistant that automates writing test cases from project documentation. Use when the user wants to generate test cases from requirements, runs... It is an AI Agent Skill for Claude Code / OpenClaw, with 310 downloads so far.

How do I install Casely?

Run "/install casely" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Casely free?

Yes, Casely is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Casely support?

Casely is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Casely?

It is built and maintained by JohnWayneeee (@johnwayneeee); the current version is v0.1.0.

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