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data-juicer

Data-Juicer repo router for local recipes, Ray recovery, and service/MCP workflows.

The English summary is being prepared. Showing the original description.

VectorSpaceLab/AREX-Skill
See how to install

Files included (28)

  • SKILL.md2.0 KB
  • references/api-reference.md1.2 KB
  • references/cli-reference.md956 B
  • references/install-and-scope.md2.1 KB
  • references/optional-extras.md1.5 KB
  • references/package-overview.md1.2 KB
  • references/repo-provenance.md2.2 KB
  • references/repo-routing-metadata.json486 B
  • references/troubleshooting.md1.4 KB
  • references/workflow-map.md809 B
  • scripts/check_environment.py2.2 KB
  • sub-skills/ray-and-recovery/references/checkpointing.md1.2 KB
  • sub-skills/ray-and-recovery/references/job-management.md713 B
  • sub-skills/ray-and-recovery/references/troubleshooting.md918 B
  • sub-skills/ray-and-recovery/references/workflows.md1.0 KB
  • sub-skills/ray-and-recovery/scripts/ray_smoke.py953 B
  • sub-skills/ray-and-recovery/SKILL.md1.7 KB
  • sub-skills/recipes-and-ops/references/cli-reference.md826 B
  • sub-skills/recipes-and-ops/references/configuration.md1.4 KB
  • sub-skills/recipes-and-ops/references/troubleshooting.md1.1 KB
  • sub-skills/recipes-and-ops/references/workflows.md1.3 KB
  • sub-skills/recipes-and-ops/SKILL.md1.7 KB
  • sub-skills/service-mcp/references/api-service.md1.4 KB
  • sub-skills/service-mcp/references/mcp.md772 B
  • sub-skills/service-mcp/references/operator-discovery.md944 B
  • sub-skills/service-mcp/references/troubleshooting.md1.0 KB
  • sub-skills/service-mcp/scripts/start_api_service.py6.0 KB
  • sub-skills/service-mcp/SKILL.md1.7 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Data-Juicer Repo Skill

Use this skill as the top-level router for the Data-Juicer repository. Keep workflow depth, long examples, and troubleshooting details in the sub-skills and shared references.

Start with the route

User needRead
Local recipe processing, dataset config, export, operator choice, or simple analysissub-skills/recipes-and-ops/SKILL.md
Ray execution, partitioning, checkpointing, job monitoring, or recoverysub-skills/ray-and-recovery/SKILL.md
FastAPI service, MCP server, operator search, or request encodingsub-skills/service-mcp/SKILL.md

Quick environment check

Install guidance lives in references/install-and-scope.md; start with py-data-juicer and add tools or distributed only when the selected route needs them.

Use the bundled smoke check when you only need a safe install/import sanity check:

python scripts/check_environment.py

Useful CLI help checks:

dj-process --help
dj-analyze --help
dj-install --help
dj-mcp --help

Shared references

  • references/repo-provenance.md
  • references/repo-routing-metadata.json
  • references/install-and-scope.md
  • references/package-overview.md
  • references/cli-reference.md
  • references/api-reference.md
  • references/optional-extras.md
  • references/troubleshooting.md
  • references/workflow-map.md

Scope boundaries

  • Do not mix local recipe guidance with Ray recovery details.
  • Do not mix HTTP/MCP request transport with local dataset semantics.
  • Do not assume optional extras are installed unless the workflow needs them.
  • Do not depend on the source checkout remaining present once the skill is created.

When in doubt

Start from references/workflow-map.md, then open the matching sub-skill.

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