工作成果数据化与简历亮点改写|简诗 AI

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Find opportunities to add metrics and estimate numbers when exact data is unavailable. Use when the user wants to quantify achievements, add numbers, percentages, or impact metrics

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按资料字段整理

工作成果数据化与简历亮点改写|简诗 AI是内容创作类的 Agent Skill,安装方式未标注,权限级别未标注,许可证不明确,有可直接复制的安装命令。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

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安装

未标注
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
skillhub install user_fccf428b/resume-quantifier
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    执行上面的命令安装;也可以把仓库里的 SKILL.md 手动放进客户端的 skills 目录。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

内容创作
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方user_fccf428b仓库 未标注 · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式未标注安装包 community
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验未标注上游最后核验时间 · 数据更新 1791665661
正文体量8.9 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
写文章与脚本

按主题产出初稿与分镜脚本。

改稿与润色

把草稿改顺、统一语气。

多平台文案改写

同一内容按平台改成长短不同的版本。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 有可直接复制的安装命令,不用自己翻文档找入口。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在内容创作场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
工作成果数据化与简历亮点改写|简诗 AI当前 未标注权限 未标注 未标注 未标注 有
AI 视频生成 调用外部服务 GitHub 仓库 431.3 万 Codex、Claude、Cursor 有
视频帧 联网访问 ClawHub 市场 262.1 万 OpenClaw 有
Markdown 转换器 写入文件 ClawHub 市场 135.3 万 OpenClaw 有
哔哩哔哩全合一 接触敏感数据 ClawHub 市场 64.1 万 OpenClaw 有
Remotion video toolkit 命令行 浏览器控制 ClawHub 市场 63.9 万 OpenClaw 有

SKILL.md 全文

8.9 KB
模型实际读到的说明书原文,来自技能仓库

Resume Quantifier

When to Use This Skill

Use this skill when the user:
- Needs to add metrics and numbers to their resume
- Has bullets without quantifiable results
- Doesn't know what numbers to include
- Says they "don't have metrics" or "can't measure impact"
- Mentions: "add metrics", "quantify", "add numbers", "measure impact", "no data"

Core Capabilities

  • Find hidden metrics in any experience
  • Estimate numbers when exact data unavailable
  • Create before/after comparisons
  • Identify measurable impact points
  • Transform vague statements into quantified achievements
  • Guide users to discover their metrics

Why Quantification Matters

The Problem:
- "Managed projects" vs "Managed 12 projects worth $2M"
- "Improved processes" vs "Reduced cycle time by 40%"
- "Helped customers" vs "Resolved 50+ tickets daily with 98% satisfaction"

Studies Show:
- Resumes with numbers get 30% more attention
- Quantified bullets are 40% more memorable
- Numbers provide credibility and scale

The Quantification Framework

Categories of Metrics

1. Money
- Revenue generated
- Costs reduced/saved
- Budget managed
- Deal sizes closed
- Profit margins improved

2. Time
- Hours saved
- Cycle time reduced
- Project duration
- Response times
- Time to market

3. Percentages
- Growth rates
- Improvement percentages
- Efficiency gains
- Error reduction
- Conversion rates

4. Volume/Scale
- Number of customers/users
- Projects managed
- Team size
- Transactions processed
- Items produced

5. Quality
- Satisfaction scores
- Error rates
- Accuracy rates
- Compliance rates
- SLA adherence

6. Frequency
- Per day/week/month
- Annual totals
- Meeting cadences
- Report cycles

Finding Hidden Metrics

The Discovery Questions

For any experience, ask:

Scale Questions:
- How many people/projects/customers?
- What was the budget/revenue involved?
- How large was the team?
- How many locations/regions?

Impact Questions:
- What changed because of your work?
- What would have happened without you?
- What problems did you solve?
- What got better/faster/cheaper?

Comparison Questions:
- How was it before vs. after?
- How did you compare to others/previous results?
- What was the baseline you improved?

Role-Specific Metric Discovery

Sales:
- Quota attainment percentage
- Revenue generated
- Number of deals closed
- Average deal size
- Pipeline generated
- New accounts acquired
- Retention rate

Marketing:
- Leads generated
- Campaign ROI
- Engagement rates
- Follower growth
- Website traffic increase
- Conversion rates
- Brand awareness metrics

Customer Service:
- Tickets resolved per day
- Customer satisfaction score
- Average response time
- First call resolution rate
- NPS score contribution

Operations:
- Efficiency improvements
- Cost reductions
- Process cycle times
- Error rate reductions
- Throughput increases

Engineering:
- System uptime
- Performance improvements
- Bug resolution rate
- Deployment frequency
- Code coverage

Project Management:
- Number of projects
- Budget sizes
- Team sizes
- On-time delivery rate
- Stakeholders managed

HR/Admin:
- Hiring numbers
- Time to fill
- Employee satisfaction scores
- Training completion rates
- Onboarding efficiency

Estimation Techniques

When you don't have exact numbers:

Conservative Estimation

Principle: Estimate low to maintain credibility

Example:
- You think you saved 100 hours/month → say "75+ hours"
- You think growth was 50% → say "~40%"
- You think you served 500 customers → say "400+"

Range Estimation

Format: "X-Y" or "X to Y"

Examples:
- "Managed team of 8-12"
- "Generated $100K-$150K in revenue"
- "Saved 20-30 hours weekly"

Minimum Bound

Format: "X+" or "at least X"

Examples:
- "Served 100+ customers daily"
- "Managed at least 15 concurrent projects"
- "Generated $500K+ in annual revenue"

Percentage of Activity

Format: Calculate from known totals

Example:
- Company had 1000 customers → You managed 20% → "Managed 200 customer accounts"
- Team had 10 people → You supervised 4 → "Supervised 40% of team"

Time-Based Calculation

Format: Work backwards from frequency

Example:
- Met with 5 clients/week × 50 weeks = "Consulted with 250+ clients annually"
- Processed 30 invoices/day × 250 days = "Processed 7,500+ invoices annually"

Quantification Templates

Before and After Template

"Improved [X] from [before number] to [after number], resulting in [Y]% improvement"

Example:
"Improved page load time from 8 seconds to 2 seconds, resulting in 75% reduction and 20% increase in user engagement"

Scale Template

"[Verb] [number] [things], resulting in [impact]"

Example:
"Managed 25 concurrent projects worth $3M, delivering 95% on-time with zero budget overruns"

Volume + Impact Template

"Processed [number] [items] per [time period], achieving [quality metric]"

Example:
"Resolved 50+ customer tickets daily, maintaining 98% satisfaction rating and 4-hour average response time"

Comparison Template

"Ranked #[X] out of [Y] in [metric], [context]"

Example:
"Ranked #2 out of 45 sales representatives nationally, generating $3.2M in annual revenue"

Common "I Have No Numbers" Situations

Situation 1: "I was just one person on a team"

Solution: Focus on YOUR contribution

Example:
- "Part of team that launched product" →
- "Contributed 40% of front-end code for product launch reaching 100K users"

Situation 2: "I don't have access to business metrics"

Solution: Quantify activities and inputs

Example:
- "Supported sales team" →
- "Created 50+ sales presentations and managed pipeline of 200+ prospects in Salesforce"

Situation 3: "My job didn't produce measurable outcomes"

Solution: Measure the work itself

Example:
- "Wrote documentation" →
- "Produced 75-page technical documentation reducing new hire onboarding time by 2 weeks"

Situation 4: "Results were confidential"

Solution: Use percentages or ranges

Example:
- "Increased revenue" →
- "Grew revenue by 40%+ year-over-year" or "Contributed to $X-$Y million growth"

Situation 5: "I was entry-level with limited impact"

Solution: Quantify learning, throughput, accuracy

Example:
- "Entered data" →
- "Processed 200+ records daily with 99.5% accuracy rate, exceeding team average by 15%"

Output Format

When quantifying a resume:

# RESUME QUANTIFICATION

## Analysis Summary
**Bullets without numbers:** X
**Bullets with numbers:** Y
**Target:** 100% of bullets should have at least one metric

## Quantified Bullets

### Original Bullet #1:
"Managed customer accounts"

### Questions to Find Metrics:
- How many accounts? → [User answer: ~40]
- What was the revenue? → [User answer: ~$2M]
- What results did you achieve? → [User answer: retained most]

### Quantified Version:
"Managed portfolio of 40 enterprise accounts representing $2M ARR, achieving 95% retention rate"

### Metrics Added:
- Account count: 40
- Revenue: $2M ARR
- Retention: 95%

---

### Original Bullet #2:
[Continue for each bullet]

## Estimation Notes
- [Metric]: Estimated based on [reasoning]
- [Metric]: Conservative estimate using [method]

## Remaining Questions
- [Questions to ask user for missing information]

Quantification Quality Checklist

For each bullet:
- ✅ Has at least ONE number
- ✅ Number is relevant (not just any number)
- ✅ Scale is clear (what does the number mean?)
- ✅ Estimation is conservative and defensible
- ✅ Number adds credibility, not confusion
- ✅ You can explain the number in an interview

Numbers to Avoid

  • ❌ Numbers that make you look bad
  • ❌ Numbers you can't explain or defend
  • ❌ Numbers that reveal confidential information
  • ❌ Exaggerated or inflated numbers
  • ❌ Numbers without context (e.g., "increased by 300%" without baseline)
  • ❌ Too many numbers in one bullet (2-3 max)

Key Principle

Every bullet can be quantified. If you think your work can't be measured, you haven't asked the right questions yet.

The goal isn't to have impressive numbers—it's to have SPECIFIC numbers that show the scope and impact of your work.

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常见问题

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答案由本站依据条目字段整理
工作成果数据化与简历亮点改写|简诗 AI怎么安装?

在支持 Skills 的客户端里执行:skillhub install user_fccf428b/resume-quantifier。安装方式为未标注。装完刷新技能列表或重开客户端。

工作成果数据化与简历亮点改写|简诗 AI支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

工作成果数据化与简历亮点改写|简诗 AI权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

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工作成果数据化与简历亮点改写|简诗 AI用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

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