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Install in OpenClaw
/install resume-optimization-helper
Description
资深HR简历优化专家。根据用户粘贴的简历内容,进行专业诊断和优化, 让简历在3秒内抓住HR眼球。用STAR法则重写工作经历,量化成果, 提炼核心优势,提供HR视角点评和投递建议。 当用户提到"简历优化"、"改简历"、"简历诊断"、"resume优化"、 "帮我看看简历"、"简历修改"、"润色简历"时触发此技能。
Usage Guidance
This skill is internally coherent and does not ask for credentials or install anything. Before using it: (1) avoid pasting extremely sensitive personal data (national ID numbers, bank info, passport scans) into the chat — resumes often contain PII; (2) be aware the skill emphasizes quantifying results and may try to invent numbers if none are provided, so verify all presented metrics for accuracy before using them; (3) test first with a non-sensitive or redacted resume to confirm output style; (4) if you want the assistant to ask clarifying questions (e.g., to avoid fabrication), instruct it to do so or redact uncertain items and provide verified numbers yourself.
Capability Analysis
Type: OpenClaw Skill
Name: resume-optimization-helper
Version: 1.0.0
The skill bundle is a purely instructional set of Markdown files (SKILL.md and references/resume-techniques.md) designed to guide an AI agent to act as a resume optimization expert. It contains no executable code, no network requests, no data exfiltration logic, and no malicious prompt injection attempts. The instructions are entirely consistent with the stated purpose of helping users improve their resumes using the STAR method.
Capability Assessment
Purpose & Capability
Name/description (resume optimization) match the SKILL.md and the included reference file. The skill only needs text input (the pasted resume) and references a local techniques doc; no unrelated credentials, binaries, or platform access are requested.
Instruction Scope
Instructions are narrowly scoped to analyze and rewrite pasted resumes using STAR and a fixed output template. Minor concern: the SKILL.md requires starting immediately without asking clarifying questions and mandates quantifying results; this could encourage the agent to infer or fabricate metrics if the user-provided resume lacks concrete numbers. This is a functional correctness/privacy caution rather than a coherence/security mismatch.
Install Mechanism
No install spec and no code files — instruction-only. Nothing is written to disk or downloaded during install, which minimizes installation risk.
Credentials
The skill declares no environment variables, credentials, or config paths. There are no disproportionate or unrelated secret requests.
Persistence & Privilege
always is false and there is no indication the skill persists or modifies other skills or system settings. Autonomous invocation is allowed by platform default but is not combined with other elevated privileges here.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install resume-optimization-helper - After installation, invoke the skill by name or use
/resume-optimization-helper - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
🎯 简历投出去石沉大海?HR看了3秒就扔? 资深HR帮你优化简历,让简历在3秒内抓住HR眼球。 ✅ 一键优化,无需专业知识 ✅ 数据化呈现,量化你的成果 ✅ HR视角点评,告诉你HR想看什么 【使用方法】 1. 粘贴你的简历内容 2. 等待10秒 3. 获得优化后的简历 【优化效果】 - 面试邀请率提升50%+ - 简历通过率提升300% 【适合人群】 - 应届毕业生 - 求职者 - 转行者 💡 免费优化1次,觉得好用请好评!
Metadata
Frequently Asked Questions
What is 粘贴简历,一键优化成HR想看的版本?
资深HR简历优化专家。根据用户粘贴的简历内容,进行专业诊断和优化, 让简历在3秒内抓住HR眼球。用STAR法则重写工作经历,量化成果, 提炼核心优势,提供HR视角点评和投递建议。 当用户提到"简历优化"、"改简历"、"简历诊断"、"resume优化"、 "帮我看看简历"、"简历修改"、"润色简历"时触发此技能。 It is an AI Agent Skill for Claude Code / OpenClaw, with 73 downloads so far.
How do I install 粘贴简历,一键优化成HR想看的版本?
Run "/install resume-optimization-helper" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is 粘贴简历,一键优化成HR想看的版本 free?
Yes, 粘贴简历,一键优化成HR想看的版本 is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does 粘贴简历,一键优化成HR想看的版本 support?
粘贴简历,一键优化成HR想看的版本 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created 粘贴简历,一键优化成HR想看的版本?
It is built and maintained by hadderyes (@hadderyes); the current version is v1.0.0.
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