Chameleon — Resume Tailor

Chameleon is an AI project that works with Claude Code, Codex, and OpenCode. It tailors a master resume YAML to a target job description, while saving the intermediate job analysis locally for later reuse.

It is designed for one job: start from a truthful master CV, adapt the wording to match a target job description, and produce a ready-to-submit PDF without inventing experience.

What It Does 🛠️

• Keeps your master CV unchanged
• Saves a separate job-analysis JSON artifact for each application
• Creates a separate tailored YAML for each application
• Rewrites only allowed parts of the resume to match the job description's language
• Renders the tailored YAML to PDF with RenderCV
• Scores a tailored CV against a saved job analysis artifact
• Works with Claude Code, Codex, and OpenCode

Constraints 🔒

• No fabricated experience, skills, metrics, titles, or dates
• Only rewording, reordering, and emphasis changes are allowed
• The master CV is never modified during a tailoring run

Prerequisites

• Python 3.10+
• Claude Code, Codex, or OpenCode

Installation

git clone https://github.com/davidalecrim1/chameleon.git
cd chameleon
make install-tools

This creates a .venv and installs rendercv inside it.

Quick Start

1. Start Claude Code, Codex, or OpenCode

All project commands are exposed as slash commands:

• /init-cv
• /chameleon
• /tailor-cv
• /score-cv
• /render-cv

Claude Code:

claude

Codex:

codex

OpenCode:

opencode

2. Import your master CV once

If your source resume is a PDF:

/init-cv ~/Downloads/david-alecrim.pdf

If you already have a RenderCV-compatible YAML:

/init-cv ~/Documents/david-alecrim.yaml

This creates a RenderCV-compatible master file under templates/ and runs a render check.

3. Tailor for a job posting

Pass either a job URL:

/chameleon --cv david_alecrim https://jobs.example.com/senior-engineer-123

Or pasted job description text:

/chameleon "Senior Software Engineer at Acme Corp. We're looking for..."

If you have more than one master CV in templates/, specify which one to use with --cv <name>, where <name> is the filename stem before _cv.yaml:

/chameleon --cv david_alecrim https://jobs.example.com/senior-engineer-123

The /chameleon flow will:

1. Fetch and analyze the job description
2. Save a JSON artifact under output/job_analyses/<analysis_id>__<company>__<role>.json
3. Rewrite the summary, reorder experience highlights, reorder skills, and clear settings.bold_keywords if present
4. Save a tailored YAML to templates/<username>_<company>_<role>_cv.yaml
5. Render it to PDF via make render
6. Report the analysis ID, saved JSON path, tailored YAML path, and generated PDF path

4. Score a tailored CV against a saved analysis

/score-cv --analysis a7c19f2d --cv templates/david_alecrim_tempo_rust_engineer_cv.yaml

This flow will:

1. Resolve the saved analysis from output/job_analyses/
2. Extract structured evidence from the tailored YAML
3. Score the CV against the saved analysis
4. Report the final score, breakdown, and missing requirements

Local Files

Chameleon stores its working files locally in two main folders:

• templates/: local CV YAML files
• output/: local generated artifacts

Within those folders:

• templates/<name>_cv.yaml is treated as a master CV when you pass --cv <name>
• Tailored CVs are written as templates/<username>_<company>_<role>_cv.yaml
• Saved job analyses are written as output/job_analyses/<analysis_id>__<company>__<role>.json
• Rendered PDFs, HTML, Markdown, Typst, and image output land in output/

Example 🎯

The following is the master template CV rendered to PDF:

License

MIT — see LICENSE.