resume-bullet-extraction

resume-bullet-extraction is a skill for Claude Code, Codex from DanielPodolsky/ownyourcode. It costs 38 tokens per session (1,299 once invoked), scanned A, original, MIT.

A guide for turning completed technical work into concise resume bullet points. It combines an action, the work completed, its technical setting, and the result.

In plain words
What is it for?
Use it after building features, fixing problems, improving performance, or updating a portfolio or job application.
Why use it?
It helps describe accomplishments instead of merely listing job duties. It also prompts you to include measurable effects when those results are available.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/danielpodolsky/ownyourcode/resume-bullets
Any agent
npx skills add DanielPodolsky/ownyourcode --skill resume-bullets
Clone the repo
git clone --depth 1 https://github.com/DanielPodolsky/ownyourcode

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for resume-bullet-extraction

README.md
[![agentmods](https://agentmods.dev/badge/skills/danielpodolsky/ownyourcode/resume-bullets.svg)](https://agentmods.dev/skills/danielpodolsky/ownyourcode/resume-bullets)
Your own site
<a href="https://agentmods.dev/skills/danielpodolsky/ownyourcode/resume-bullets"><img src="https://agentmods.dev/badge/skills/danielpodolsky/ownyourcode/resume-bullets.svg" alt="Measured on agentmods" height="20"></a>
Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,299 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00038 $0.01299
Opus 5 $0.00019 $0.00649
Sonnet 5 $0.00008 $0.00260
Haiku 4.5 $0.00004 $0.00130

Measured 4d ago against content hash 3c414044aa97, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

resume-bullet-extraction 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 4d 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.

.claude/skills/career/resume-bullets/SKILL.md · 224 lines

How it starts

The opening of the file, as written. The whole thing — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Resume Bullet Extraction

"Your resume isn't a job description. It's a highlight reel of impact."

Purpose

Transform completed work into powerful resume bullet points that demonstrate value and technical competence.


The Bullet Formula

[Strong Action Verb] + [What You Did] + [Technical Context] + [Impact/Result]

Components

Component Purpose Example
Action Verb Shows initiative Engineered, Architected, Optimized
What You Did The accomplishment JWT authentication system
Technical Context Shows skill using React, Node.js, Redis
Impact Why it matters reducing auth errors by 40%

Strong Action Verbs

Building/Creating

  • Engineered
  • Architected
  • Developed
  • Implemented
  • Built
  • Designed

Improving

  • Optimized
  • Enhanced
  • Refactored
  • Modernized
  • Streamlined
  • Accelerated

Problem Solving

  • Resolved
  • Debugged
  • Eliminated
  • Reduced
  • Prevented
  • Mitigated

Leading/Collaborating

  • Led
  • Spearheaded
  • Collaborated
  • Mentored
  • Coordinated

Impact Quantification

Always try to quantify. If you can't measure directly, estimate reasonably.

Performance

  • "reducing load time by 60%"
  • "improving response time from 2s to 200ms"
  • "handling 10,000+ concurrent users"

Reliability

  • "achieving 99.9% uptime"
  • "eliminating production errors"
  • "reducing bug reports by 50%"

Business

  • "increasing user retention by 25%"
  • "supporting 50,000 monthly active users"
  • "saving 10 hours/week of manual work"

Scale

  • "processing 1M+ transactions daily"
  • "managing 500GB of user data"
  • "serving 100+ API endpoints"

Bullet Templates

Feature Implementation

[Verb] [feature] using [technologies] that [impact]

Examples:
- Engineered JWT authentication with refresh token rotation using Node.js and Redis, eliminating session hijacking vulnerabilities
- Built real-time notification system using WebSockets and React, improving user engagement by 35%

Read the full file on GitHub · 224 lines

Changes

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.

  1. 4d ago First seen · 224 lines · 38 tokens per session scan A 3c414044aa97

Subscribe to this mod's changes

resume-bullet-extraction is a skill published in the GitHub repository DanielPodolsky/ownyourcode (281 stars, last pushed 2mo ago), licensed MIT. It adds 38 tokens to every session and 1,299 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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