agentleFS
hyf020908hyf020908/modelscope-skills/skills/modelscope-dataset-explorer/SKILL.md

modelscope-dataset-explorer

Skill4 starsChanged 8 months agoApache-2.0View on GitHub

Explore ModelScope datasets from plain-language inspection requests using metadata lookup, selective download, and local profiling.

The file

We split this skill into the rules it gives an agent

6 rules. About 0 are common, 6 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈6

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use this skill when the user wants to understand an existing dataset before training, cleaning, or publication.

    line 8
  2. Distinctive:

    Start from metadata and only download files when inspection really needs local access.

    line 15
  3. Distinctive:

    Run local profiling or SQL queries.

    line 22
  4. Distinctive:

    Never dump sensitive rows into logs.

    line 41
  5. Distinctive:

    Never download the whole dataset when metadata or a filtered subset is enough.

    line 42
  6. Distinctive:

    Never recommend a dataset without mentioning real caveats.

    line 43

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

ModelScope Dataset Explorer

Use this skill when the user wants to understand an existing dataset before training, cleaning, or publication.

Request Style

  • Accept requests such as:
    • Find a Chinese instruction dataset for SFT.
    • 检查这个数据集的列、切分和样本质量。
  • Start from metadata and only download files when inspection really needs local access.

Workflow

  1. Resolve the target dataset from the request.
  2. Inspect metadata first.
  3. Download only the smallest useful subset.
  4. Run local profiling or SQL queries.
  5. Return concrete findings, not generic praise.

What To Report

  • dataset id
  • split layout
  • schema summary
  • file formats
  • representative samples when safe
  • concrete risks such as duplicates, imbalance, missing fields, or license ambiguity

Tools

  • ModelScope metadata APIs or CLI download
  • DuckDB for parquet/csv/jsonl profiling

Guardrails

  • Never dump sensitive rows into logs.
  • Never download the whole dataset when metadata or a filtered subset is enough.
  • Never recommend a dataset without mentioning real caveats.

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