Parse XLSX test documentation into a structured JSON manifest.
npx skills add https://github.com/midas44/ttt-expert-v2 --skill xlsx-parser
Please help me install this Agent Skill. Skill: xlsx-parser Source: https://github.com/midas44/ttt-expert-v2/tree/main/.claude/skills/xlsx-parser Command: npx skills add https://github.com/midas44/ttt-expert-v2 --skill xlsx-parser
Parse XLSX test documentation into a JSON manifest for test automation. Use this skill when you need to convert module-specific XLSX workbooks from test-docs/ into a structured manifest consumed by the autotest generator, refresh manifests, or assess test coverage.
Run the parser by executing the command to process XLSX files into manifest.json (the exact command is provided in the script notes).
High-intent search queries and answers about installing and using this skill.
To convert XLSX test documentation into a structured JSON manifest, you can use a parser that reads .xlsx workbooks, iterates through sheets, and extracts test-case data like IDs, modules, steps, and expected results into a single output file.
Yes, parsing XLSX test cases with merged cells and multi-line step descriptions is supported to preserve data fidelity. The parser handles these worksheet complexities while extracting structured test-case data into the manifest.
The best way to generate a test automation manifest from multiple Excel workbooks is to run a parser that reads all .xlsx files from your input directory, extracts structured test-case data across modules, and outputs a single consolidated JSON manifest.
You need to refresh an existing test automation manifest when new test documentation is added to your input directory. Running the parser produces an up-to-date manifest for autotest generation and coverage assessment.
Yes, the parser extracts preconditions, priorities, and tags from test docs. It maps test cases to modules, IDs, titles, steps, and expected results to ensure comprehensive structured data for automation.
Parsing XLSX test docs into JSON helps with test coverage assessment by structuring scattered workbook data into a unified manifest. This structured output enables analytics and validates existing manifests against current documentation.
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