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Guides fast exploration of tabular CSV data for lead-style or operational lists. Use when the user works with sample-data/leads-sample.csv, mentions CSV analysis, lead lists, filtering, or summarizing spreadsheet exports.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Orients newcomers to this teaching repository and AI-assisted workflows (chat, agent tasks, project skills). Use when the user is new to the repo, asks how to start, what this project demonstrates, or how to preview the demo site.
Guides fast exploration of tabular CSV data for lead-style or operational lists. Use when the user works with sample-data/leads-sample.csv, mentions CSV analysis, lead lists, filtering, or summarizing spreadsheet exports.
Orients newcomers to this teaching repository and Cursor’s workflow (chat, Agent mode, skills, terminal). Use when the user is new to Cursor, asks how to start, what this repo is for, or how to preview the demo site.
| name | analyze-csv-sample |
| description | Guides fast exploration of tabular CSV data for lead-style or operational lists. Use when the user works with sample-data/leads-sample.csv, mentions CSV analysis, lead lists, filtering, or summarizing spreadsheet exports. |
sample-data/leads-sample.csv)Example B2B-style leads: company, contact, industry, geography, size, pipeline stage, and dates. Fictional data using example.com emails.
A — Conversation
Ask for counts by industry / region, filters on stage, or top companies by employees.
B — Script
From repo root:
python3 scripts/quick_csv_summary.py sample-data/leads-sample.csv
Uses Python’s standard library only (see scripts/quick_csv_summary.py).
For broader CSV workflows (exports from CRMs, spreadsheets), the same pattern applies: summarize → filter → export subsets.