Use this skill when the user:
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionresume-quantifierExecute the skills CLI command in your project's root directory to begin installation:
Fetches resume-quantifier from paramchoudhary/resumeskills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate resume-quantifier. Access via /resume-quantifier in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Run in your terminal
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Use this skill when the user:
The Problem:
Studies Show:
1. Money
2. Time
3. Percentages
4. Volume/Scale
5. Quality
6. Frequency
For any experience, ask:
Scale Questions:
Impact Questions:
Comparison Questions:
Sales:
Marketing:
Customer Service:
Operations:
Engineering:
Project Management:
HR/Admin:
When you don't have exact numbers:
Principle: Estimate low to maintain credibility
Example:
Format: "X-Y" or "X to Y"
Examples:
Format: "X+" or "at least X"
Examples:
Format: Calculate from known totals
Example:
Format: Work backwards from frequency
Example:
"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"
"[Verb] [number] [things], resulting in [impact]"
Example:
"Managed 25 concurrent projects worth $3M, delivering 95% on-time with zero budget overruns"
"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"
"Ranked #[X] out of [Y] in [metric], [context]"
Example:
"Ranked #2 out of 45 sales representatives nationally, generating $3.2M in annual revenue"
Solution: Focus on YOUR contribution
Example:
Solution: Quantify activities and inputs
Example:
Solution: Measure the work itself
Example:
Solution: Use percentages or ranges
Example:
Solution: Quantify learning, throughput, accuracy
Example:
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]
For each bullet:
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.
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
resume-quantifier fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added resume-quantifier from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: resume-quantifier is focused, and the summary matches what you get after install.
Solid pick for teams standardizing on skills: resume-quantifier is focused, and the summary matches what you get after install.
resume-quantifier is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
We added resume-quantifier from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in resume-quantifier — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
resume-quantifier has been reliable in day-to-day use. Documentation quality is above average for community skills.
resume-quantifier fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend resume-quantifier for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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