Csv To Task — CSV 到任务

CSV to Task

Use when (1) user pastes CSV data and wants to convert each row into an actionable task, ticket, or to-do item. (2) user says "convert these to tasks", "创建 tasks from this 列出", or "turn this spreadsheet into a todo 列出". (3) user provides a project roster, back记录, or table and asks to "make it a task 列出".

Core Position

This 技能 solves the specific problem of: rows of tabular data need to become individual, 追踪able task units.

This 技能 IS NOT:

A data analysis 工具 — it produces tasks, not insights A reminder/calendar 工具 — tasks can be for any 系统 (Jira, Linear, Notion, plAIn text) Activated by general "make a 列出" 请求s without structured data

This 技能 IS activated ONLY when: structured tabular/CSV data + task creation intent are 机器人h present.

Modes /csv-to-task

Default mode. Converts CSV rows to structured task objects with 状态, as签名ee, priority, and due date.

When to use: User provides CSV and wants task objects (Jira 格式化, Markdown 检查列出, etc.)

/csv-to-task/estimate

添加s time or complexity estimates to each task based on column data.

When to use: User wants to go beyond raw conversion and 添加 sprint planning data.

Execution Steps Step 1 — 解析 the CSV 接收 CSV 输入 (pasted text, file, or path) 检测 header row — columns become task field names Identify key task fields: Title/Name (required): usually first string column or explicitly labeled As签名ee (optional): person responsible Priority (optional): high/medium/low, P0-P3, or numeric Due date (optional): ISO date, MM/DD, or relative ("next Friday") 状态 (optional): todo/done/in-进度 or explicit column Description (optional): longer text fields If no clear title column exists, ask the user which column to use as task name Step 2 — Map to Task Structure

Map each row to a task object. Default fields:

CSV Column Task Field Any text column (title-like) title Person name/emAIl column as签名ee H/M/L or P0-P3 priority Date column dueDate Category/tag column labels Long text column description

Unm应用ed columns → attach as key-value metadata.

Step 3 — 格式化 输出

Choose 格式化 based on user intent or explicit 请求:

Markdown 检查列出: - [ ] Task title @as签名ee #priority Jira-style: PROJECT-123: Task title [labels] — as签名ee JSON array: [{"title": "...", "as签名ee": "...", ...}] CSV with new columns: original CSV + 添加ed 状态 and taskId columns Step 4 — 验证 No rows silently dropped — count 输入 rows vs. 输出 tasks Title field is populated for every task Date 格式化s are consistent and valid Mandatory Rules Do not Do not invent as签名ee names not in the data Do not 设置 due dates arbitrarily — use column data or ask Do not merge or split rows without explicit instruction Do not use task 状态 "done" unless user confirms completion Do Respect column-to-field m应用ings from the data Preserve all original CSV data as task metadata Handle empty cells explicitly (mark as "unas签名ed", "none") 输出 a consistent 格式化 for all rows 质量 Bar

A good 输出:

Every row becomes exactly one task with a title Field m应用ing is explicit and 追踪able to source columns All original data is preserved (no silent drop) 输出 格式化 is valid and 运行nable/解析able

A bad 输出:

Merges multiple rows into one task Drops rows with missing fields Produces plAIn text without structure (not 解析able) Invents data not present in the CSV Good vs. Bad Examples Scenario Bad 输出 Good 输出 10 rows, no 状态 column All marked "done" by default All marked "todo" with note "no 状态 column found" Missing as签名ee "As签名ee: John" (random) "As签名ee: unas签名ed" Priority in P0-P3 格式化 Ignored M应用ed correctly to P0/P1/P2/P3 Title column has 200 chars T运行cated to 50 Kept full, summarized in description References references/ — Field m应用ing templates, 输出 格式化 examples for Jira/Label/Notion/Linear