Borrowing it
Nothing to install: this file belongs to opencue/cuecards. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/opencue/cuecards/main/.agents/skills/resume-quantifier/SKILL.mdgit clone --depth 1 https://github.com/opencue/cuecardsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/opencue/cuecards/resume-quantifier)<a href="https://agentmods.dev/skills/opencue/cuecards/resume-quantifier"><img src="https://agentmods.dev/badge/skills/opencue/cuecards/resume-quantifier.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00017 | $0.02013 |
| Opus 5 | $0.00009 | $0.01007 |
| Sonnet 5 | $0.00003 | $0.00403 |
| Haiku 4.5 | $0.00002 | $0.00201 |
Grade A, and why
resume-quantifier scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to resume-quantifier — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 351 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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?
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 351 lines · 17 tokens per session scan A 6cdf56f990ff
resume-quantifier is a skill published in the GitHub repository opencue/cuecards (5 stars, last pushed today), licensed MIT. It adds 17 tokens to every session and 2,013 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to resume-quantifier, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
loongsuite-pilot-insight
A reporting workflow for turning LoongSuite Pilot and AI coding-agent logs into structured reports about events, teams, data quality, development efficiency, and AI use. It defines the meaning of the log fields and the measurements used in dashboards.
loongsuite-pilot-ops
Skill "loongsuite-pilot-ops" from alibaba/loongsuite-pilot, covering loongsuite-pilot-ops, quick start, todo: add quick start commands and usage.
atomic-visual-options
Planning-phase visual comparison aid. Renders 2-4 side-by-side variants per decision dimension as a single throwaway, self-contained HTML file and captures the user's pick as typed terminal codes (e.g. "A2 B3"). Auto-fires on phrases like "show me a few options", "mock up some variants", "let me see this side by…
atomic-wiki
Conversational wiki and capture-bucket routing. Fires when the user wants a place, space, or folder for notes, research, tickets, raw dumps, or knowledge capture — checks the block in /.claude/CLAUDE.md; if the cwd is under a registered realm, creates the folder as a bucket via atomic wiki bucket add rather than a…
atomic-review
Compressed code review comments. Cuts noise from PR feedback while preserving the actionable signal. Each comment is one line: location, problem, fix. Use when user says "review this PR", "code review", "review the diff", or invokes /atomic-review. Auto-triggers when reviewing pull requests.
atomic-tdd
Test-first discipline. Auto-triggers on "let's implement X", "add feature Y", "fix bug Z", "write a test for", "implement", "build out", and similar pre-code-change phrases. Iron rule: failing test exists before production code. Skip only for pure docs/config changes with an explicit "skipped because:" note. Explicit…