resume

resume is a command for Claude Code from noamseg/interview-coach-skill. It costs 0 tokens per session (4,451 once invoked), scanned A, original, MIT.

A command for improving a job applicant's resume across formatting, wording, keywords, seniority, and consistency. An ATS is software employers use to read, search, and rank resumes before recruiters review them.

In plain words
What is it for?
Use it to improve resume sections and bullets, increase relevant keyword coverage, fix parsing risks, address concerns, and keep the resume consistent across applications and profiles.
Why use it?
It addresses problems that can hide good experience from resume-screening software or busy recruiters. It also helps make achievements clearer and align the resume with the candidate's level and target roles.

Command for Claude Code

Written for Claude Code: a Claude Code command (commands/*.md).

Good fit Use it to improve resume sections and bullets, increase relevant keyword coverage…

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/noamseg/interview-coach-skill/resume
About the project

Interview Coach is a Claude Code-based coaching system for the full job-search process, including job-description analysis, application materials, interview practice, answer evaluation, and offer negotiation. It is intended for job seekers who want tailored feedback and structured preparation based on their own experience and interview transcripts. Its catalogue entry consists of commands, a setting, and a skill that provide the coaching workflows.

noamseg/interview-coach-skill · 2,124 stars · on GitHub

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.

Clone the repo
git clone --depth 1 https://github.com/noamseg/interview-coach-skill

Made for: Claude Code.

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

README.md
[![agentmods](https://agentmods.dev/badge/commands/noamseg/interview-coach-skill/resume.svg)](https://agentmods.dev/commands/noamseg/interview-coach-skill/resume)
Your own site
<a href="https://agentmods.dev/commands/noamseg/interview-coach-skill/resume"><img src="https://agentmods.dev/badge/commands/noamseg/interview-coach-skill/resume.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 4,451 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00000 $0.04451
Opus 5 $0.00000 $0.02226
Sonnet 5 $0.00000 $0.00890
Haiku 4.5 $0.00000 $0.00445

Measured 7d ago against content hash 765d1eb272c3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

resume 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 7d 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.

references/commands/resume.md · 396 lines

How it starts

The opening of the file, as written. The whole thing — 396 lines — stays where its author put it; the contents beside it link to each section on GitHub.

resume — Holistic Resume Optimization

Optimize the candidate's resume across every dimension that actually affects whether they get interviews: ATS parsing and ranking, recruiter scan behavior, bullet quality, seniority calibration, keyword coverage, structure, concern management, and cross-surface consistency. This is NOT a duplicate of kickoff's Step 2.5 (which reads the resume for coaching signals). This is an optimization of the resume itself as a job-search document.

Also read references/differentiation.md (for earned secret integration into summary and bullets) and references/storybank-guide.md (for storybank data to feed into bullet rewrites and quantification).


How Resumes Actually Work

ATS (Applicant Tracking Systems): 83% of companies use AI-assisted screening. Most ATS don't auto-reject — they rank. Recruiters search the top and never see the rest. Average ATS score is 37%; target 75-80%. Keyword matching ranges from literal (Taleo) to semantic (iCIMS). Tables, columns, text boxes, headers/footers break parsing. Non-standard section headers lose scoring weight.

Recruiter Scan: 7-11 seconds, F-pattern. 80% of attention goes to: name, current title/company, previous titles/companies, dates, education. Quantified achievements increase callbacks 40%. 49% auto-dismiss for spelling/grammar. 72% prefer bullets over paragraphs.

Bullet Quality: XYZ formula (Accomplished X measured by Y by doing Z). "So What?" test (3 escalations: "So what?" → "Why does that matter?" → "What changed because of this?"). Action verbs shape 60%+ of perceived seniority. Quantification without hard numbers: ranges, frequency, scope, proxy metrics, comparative language.

Seniority Signaling: IC ("developed/built/implemented") → Manager ("managed/led/coordinated") → Director ("directed/scaled/established") → VP ("championed/orchestrated/transformed"). Beyond verbs: scope of impact, budget responsibility, span of control, strategic vs. tactical language.

Read the full file on GitHub · 396 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. 7d ago First seen · 396 lines · 0 tokens per session scan A 765d1eb272c3

Subscribe to this mod's changes

resume is a command published in the GitHub repository noamseg/interview-coach-skill (2,124 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 4,451 tokens. 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.