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Synchronized multi language test data directory

Skill kjuhwa/skills-hub/skills/testing/synchronized-multi-language-test-data-directory

Single tests_data/ tree with one subdir per content type, shared across every language test suite, plus reference outputs and known-failure buckets.From its SKILL.md

Install
npx -y skills add kjuhwa/skills-hub --skill synchronized-multi-language-test-data-directory

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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SKILL.md

1.8 KB, 299 tokens by cl100k_base, as published. Nobody here has run it

Synchronized Multi Language Test Data Directory

Trigger: Multi-language project where every binding must be tested against the same corpus to guarantee parity.

Steps

  • Organize tests_data/basic/<content-type>/ with 1–3 small sample files per type.
  • Add tests_data/current_missdetections/ for known-bad cases and tests_data/previous_missdetections/ for regressions.
  • Commit reference outputs (predictions + features) under tests_data/reference/ as JSONL.
  • In every binding's test suite, iterate over the subdirs and verify detection.
  • Set .gitattributes to keep binary samples binary and text samples LF-only — CRLF auto-conversion will corrupt your corpus.
  • Periodically audit current_missdetections/ and graduate passing files into basic/.

Counter / Caveats

  • Test files inflate repo size; cap at ~100KB each or use git-lfs.
  • Some types need rich examples (PDF/DOCX with text+images+metadata); others need a single byte.
  • CRLF/LF line ending drift silently breaks reference comparisons.
  • Maintaining the corpus is manual labor; budget time per release to keep it healthy.

Source

Extracted from magika (https://github.com/google/magika.git @ main).

Files of interest:

  • tests_data/basic/ (per-content-type subdirs)
  • tests_data/features_extraction/
  • python/tests/
  • go/cli/cli_test.go

What ships with it: 1 file

923 B alongside SKILL.md

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