菜单
Use this skill for CSV data analysis tasks that require reading a local CSV file, checking row counts and columns, grouping records, computing rates or aggregates, creating a chart, and writing a short Markdown report.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/zjunlp/DataMind --skill csv-analysis命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Self-evaluate the current agent on LongDS-Bench (zjunlp/DataMind): the long-horizon, multi-turn agentic data-analysis benchmark. Use this when the user asks to run, score, or benchmark an agent on LongDS / LongDS-Bench / DataMind longds, or to measure multi-turn data-analysis ability. This does NOT use DSGym's Docker runtime — the agent running this skill IS the agent under test: it reads a locally-prepared dataset, performs the multi-turn analysis with its own tools, and is scored by the official LLM-judge rule. The ~19.5 GB dataset must be downloaded and prepared by the operator beforehand (see `$SKILL_DIR/../README`); this skill does not download it. Heavyweight and long-running; run in the background if supported and confirm scope first.
Solve questions about which fee IDs apply to a payment merchant, transaction characteristics, or time period in the dabstep dataset. Use this skill for any question asking "which fee IDs apply to X", "what are the applicable fee IDs for merchant Y", "which merchants are affected by fee Z", or any query involving filtering fees.json based on payment characteristics or merchant attributes.
Solve dabstep Average_Fee_Estimation problems. Use this skill for questions asking about average payment processing fees, which card scheme is cheapest/most expensive in an average scenario, and fee calculations based on card scheme, account type, MCC description, credit/debit type, or any combination of these filters.
基于 SOC 职业分类
正在显示 SKILL.md
| name | csv-analysis |
| description | Use this skill for CSV data analysis tasks that require reading a local CSV file, checking row counts and columns, grouping records, computing rates or aggregates, creating a chart, and writing a short Markdown report. |
Use this workflow when the user asks for analysis over a local CSV file.
failure_rate = number of rows where results == "Fail" / number of rows in the group
facility_type, include only groups that meet the user's minimum inspection-count threshold.failure_rate descending, inspection_count descending, facility_type ascending
source file path
total rows read
number of facility_type groups before and after filtering
chart file exists
report file exists
For the demo task, create:
outputs/summary.md
outputs/failure_rate_by_facility.png
The report should include: