360 Secure SkillHub
360 安全技能中心

Convert Spreadsheet Rows

核心功能是将电子表格行数据转换为Jira任务、Markdown或JSON等结构化对象,涵盖解析验证输入、格式规则转换、处理缺失字段/特殊字符等边缘情况,输出带字段映射摘要。典型场景包括批量生成Jira任务、表格数据转文档或结构化数据。支持--pretty(格式化输出)和--strict(结构不符即报错)模式,输入为JSON/CSV等格式数据,输出确保格式有效、数据无损。

wangjipeng977
wangjipeng977
热度 16.10
最近更新 2026-05-27 11:29:43
分类:效率依赖:读写文件 / 内部调用大模型应用场景:文件转换 / 数据处理 / 任务管理

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add convert-spreadsheet-rows
Metadata
name
convert-spreadsheet-rows
description
Use when (1) Convert spreadsheet rows into structured task objects for Jira. Markdown. or JSON formats.
license
MIT
metadata
{"version":"1.0","category":"productivity","author":"wangjipeng","sources":["https://github.com/MiniMax-AI/skills"]}

Core Position

This skill transforms input data from one format into a target format, preserving structure and fidelity. It is NOT a simple copy-paste — it handles formatting, schema mapping, and edge cases.

Key responsibilities:

  • Parse the input format (JSON/CSV/code/etc.) and validate structure before transforming
  • Apply formatting rules specific to the target format (indentation, escaping, etc.)
  • Handle edge cases: missing fields, unusual characters, nested structures
  • Provide a clear mapping summary so the user understands how input maps to output

Modes

/convert-spreadsheet-rows --pretty

Formatted output. Applies proper indentation, spacing, and style conventions.

/convert-spreadsheet-rows --strict

Strict mode. Fails on any deviation from expected structure rather than guessing.

Execution Steps

  1. Parse input — Read and parse the input; detect format (JSON/CSV/XML/code/etc.)
    • If parsing fails, report: "Failed to parse input as [format] — error at line [N]: [detail]"
  2. Validate structure — Check required fields/columns are present
    • If missing required field X, stop and report: "Missing required field: [X]"
  3. Transform — Convert input to target format, applying format-specific rules
    • Preserve all data — do not silently drop fields
    • Apply proper escaping for special characters (quotes, newlines, etc.)
  4. Validate output — Run the target format parser on the result to confirm it's valid
    • If output is invalid, revert to previous version and report what went wrong
  5. Deliver — Return the converted output with a brief mapping summary

Mandatory Rules

Do not

  • Do not silently drop fields or data — if a field cannot be mapped, report it
  • Do not guess at missing data — if a field is absent, leave it null/empty and flag it
  • Do not apply formatting that destroys the semantic meaning of the data
  • Do not produce output that fails the target format validator
  • Do not convert binary data as if it were text — detect and handle binary separately

Do

  • Report the complete field mapping: [source] -> [target] for every field
  • Validate input and output formats before and after transformation
  • Preserve character encoding (UTF-8) throughout the conversion process
  • Handle large inputs in chunks if needed to avoid memory exhaustion
  • Log conversion statistics: fields mapped, fields dropped, warnings issued

Quality Bar

Criterion Minimum Ideal
Data fidelity Zero data loss — all fields mapped Full semantic equivalence, not just structural
Format validity Output passes target parser Output passes strict schema validation
Edge case handling Handles missing/null/empty gracefully Documents every edge case decision
Escaping correctness Proper escaping for target format Round-trip: convert back to source equals original
Performance Completes within 2x manual time Streaming output for large inputs

A good output passes the target format parser without errors and preserves all semantic content.

Good vs. Bad Examples

Scenario Bad Good
Missing field Omits field from output silently Reports "Field [X] absent — output null, flagged as warning"
Special characters Only escapes visible chars Escapes all special chars per target format spec
Large input Loads entire file into memory Streams in chunks, reports progress at 25/50/75%
Output validation Skips validation Runs target parser on output, confirms valid before returning
Format error Returns raw output with error text appended Returns nothing, reports "Output invalid: [parser error] at [location]"