resume-roast 1.0.3

A terminal-based LLM-powered resume coaching tool

Resume Roast

A terminal-based LLM-powered resume coaching tool. Get brutal, structured feedback on your resume, refine individual bullet points through back-and-forth chat, or generate new resume blocks from scratch.

Features

• evaluate — Submit a PDF or DOCX resume and receive a structured roast: per-category scores, highlighted strengths and weaknesses, and concrete rewrite suggestions with before/after examples
• interview — Agentic behavioral interview that asks resume-tailored questions, fact-checks answers against your resume, and scores them across ownership, technical competence, problem-solving, and collaboration
• refine — Interactive chat that coaches a single resume bullet, rating it on every turn and suggesting improvements
• generate-block — Chat-based interviewer that gathers details about a role or project, then generates a formatted resume block rated against our bullet-writing principles
• Multiple LLM models to choose from, with token usage and cost reporting — per reply in the chat sessions, per run for evaluate and interview
• Configurable persona (recruiter, hiring manager, senior engineer) and level (intern through senior) for evaluations

Getting Started

Prerequisites

• Python 3.12 or higher
• An NVIDIA NIM API key (get one at build.nvidia.com)

Installation

pip install resume-roast

For development:

git clone https://github.com/jfang324/resume-roast.git
cd resume-roast
poetry install

First-Time Setup

Set your NVIDIA API key:

resume-roast config credentials

You can also configure the model, persona, seniority level, and the remaining settings:

resume-roast config settings

Configuration is stored in ~/.resume-roast/.

Usage

Commands

Command	Arguments & options	Description
evaluate <path>	<path> — PDF or DOCX resume	Roast a resume: scores, strengths/weaknesses, and rewrite suggestions
interview <path>	<path> — PDF or DOCX resume --report — save a Markdown report to ~/.resume-roast/interview-reports/	Run an agentic behavioral interview and score the answers
refine <bullet>	<bullet> — the bullet text to coach	Coach a single resume bullet through a back-and-forth chat
generate-block	(none)	Interview you about a role or project, then generate a resume block
config credentials	(none)	Set the API key for each provider
config settings	(none)	Choose each setting from its allowed values
show credentials	(none)	Print saved API keys, masked
show settings	(none)	Print every setting's current value

--debug is a global option, so it goes before the command — resume-roast --debug evaluate resume.pdf. It writes full debug logs (including raw prompts and responses containing resume content) to ~/.resume-roast/logs/debug.log.

Evaluate a Resume

resume-roast evaluate path/to/resume.pdf

Extracts your resume, sends it to the LLM for structured analysis, and prints a diff-highlighted report with scores and rewrite suggestions.

Refine a Bullet

resume-roast refine "Managed a team of 5 engineers"

Opens an interactive chat. The LLM coaches you, rating the bullet on every reply and suggesting improvements. Available commands:

Command	Action
/replace <text>	Replace the bullet with a new version (re-rates it)
/generate <notes>	Generate a candidate rewrite (notes optional)
/help	Show available commands
/exit	End the session
(plain text)	Conversational coaching turn

Generate a Block

resume-roast generate-block

Opens an interactive chat. The LLM interviews you about a role or project, asking questions to gather specifics. Type /generate when you're ready to produce a formatted resume block (header + 3-6 bullet points). /generate always produces a block, rated 0-10 — if the details are thin it still generates, then names what would raise the score. Available commands:

Command	Action
/generate <notes>	Generate a resume block (notes optional)
/help	Show available commands
/exit	End the session
(plain text)	Answer questions, add details

Interview

resume-roast interview path/to/resume.pdf

Starts an agentic behavioral interview. The LLM generates questions tailored to your resume, asks them one at a time, fact-checks your answers against the resume, and probes deeper with follow-ups when needed. After all questions, produces a competency report with per-category scores, strengths, and growth areas.

Pass --report to also save a detailed Markdown copy — verdict, per-question evidence, and fact-checks — under ~/.resume-roast/interview-reports/. The file is named by timestamp and resume (e.g. 20260723-142530-resume.md), so repeated runs accumulate without overwriting. Nothing is written if the interview ends before any answer is scored.

Available commands:

Command	Action
/exit	End the interview early

Development

See docs/development.md for setup and development commands.

Tools & Technologies

Core

• Python 3.12+
• Typer (CLI framework)
• Rich (terminal output, spinners, diff rendering)
• pymupdf4llm (PDF to Markdown extraction)
• mammoth (DOCX to Markdown extraction)
• defusedxml (safe XML parsing for DOCX metadata parts)
• openai SDK (NVIDIA NIM API client)

Code Quality

• Ruff (linting + formatting)
• Pyright (strict type checking)
• Bandit (security linting)
• pre-commit hooks

Testing

• pytest
• coverage (branch coverage, 85% minimum)
• pytest-asyncio

Build & Package

• Poetry

License

This project is licensed under the MIT License — see the LICENSE file for details.