Token导航 LogoToken导航TokenDH.com
效率需要联网clawhub未标认证来源可访问clear审计通过

cv-skill简历技能

Agent Skill

cv-skill 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

2,928

周安装

122

GitHub Stars

公开资料未说明

下载量

976
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:cv-skill(简历技能)
来源仓库:https://github.com/jasoncodespace/cv-skill
安装命令:
openclaw skills install cv-skill
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install cv-skill

简介

根据候选人信息生成哈佛风格的标准化简历文档。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

  • 适合求职辅导、简历优化与 HR 初筛材料准备。
  • 支持结构化数据输入与现有简历解析,提升格式专业性。
  • 输出内容需由用户最终审阅确认,避免信息误用。
  • cv-skill 属于效率类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
cv-skill
description
Create professional Harvard-style resumes and CVs from user-provided candidate descriptions, structured data, or existing resumes. Use when the user wants a polished one-page or role-targeted resume, needs multiple resume versions for different job directions, wants to convert raw candidate notes into structured bullets, or needs DOCX/PDF outputs in any language from structured input data.
version
1.0.0

CV Skill

Create role-targeted, black-and-white, Harvard-style resumes from candidate descriptions, structured input, or existing resumes.

Use this skill when

  • The user wants a professional resume or CV in .docx
  • The user gives a rough candidate description and wants the agent to draft the resume from scratch
  • The user wants one candidate rewritten into multiple job-targeted versions
  • The user provides a PDF, notes, or rough bullets and wants a polished resume
  • The user wants tighter, more professional bullets without fluff
  • The user wants a Harvard-style layout with larger spacing and clean hierarchy
  • The user needs output in a language other than Chinese or English

Workflow

1. Gather candidate data

Use the structured schema in references/input-schema.md.

If you are starting from an existing resume, extract:

  • contact info
  • summary / positioning
  • education
  • work experience
  • projects
  • campus or extracurricular items
  • tools, languages, certificates
  • target job directions

2. Define track-specific positioning

For each job direction, rewrite:

  • resume title
  • 2-3 sentence summary
  • bullet emphasis within experience
  • skills ordering

Keep facts intact. Do not invent results or responsibilities.

3. Generate the resume

Run:

python3 scripts/generate_resume.py --input assets/example_profile.json --track all --output-dir /tmp/cv-output

Generate a specific track:

python3 scripts/generate_resume.py --input candidate.json --track operations --output-dir /tmp/cv-output

Try PDF export when LibreOffice is installed:

python3 scripts/generate_resume.py --input candidate.json --track all --output-dir /tmp/cv-output --pdf

4. Validate before delivery

Check that:

  • no hardcoded personal info from unrelated candidates remains
  • dates and headings are consistent
  • bullets are role-targeted rather than generic
  • low-signal items are removed or pushed down
  • generated filenames are generic and safe

Layout rules

  • Single column
  • Black and white only
  • Section headers with strong hierarchy
  • Larger spacing than default Word exports
  • Short, factual bullets
  • Avoid self-evaluation phrases such as “责任心强” or “结果导向”
  • Prefer evidence and scope over adjectives

Safety rules

  • Do not hardcode real candidate data into scripts
  • Do not store secrets, API keys, tokens, or .env files in the skill folder
  • Keep outputs outside the skill folder unless the user explicitly wants examples saved there
  • Use assets/example_profile.json only as a redacted example

Files

  • scripts/generate_resume.py: generic generator
  • references/input-schema.md: input contract
  • references/rewriting-guide.md: track-specific rewriting guidance
  • assets/example_profile.json: safe sample input
  • agents/openai.yaml: UI metadata

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

79.99%
按下载量换算781

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills