Drafting #

Turn discovered jobs into tailored application drafts — email copy for direct outreach, or step-by-step guides for ATS forms (Greenhouse, Lever, Ashby, Workday, etc.).

Pages in this section #

Resume parsing

Resume parsing #

Raven parses your resume from config/profile.yml → resume.path and caches structured bullets and skills.

Supported formats #

Format	Notes
.md	Best — use ## Experience with - bullet lines
.txt	Bullet lines + optional Skills: line
.pdf	Requires pdf-parse (installed via raven setup)

Markdown structure #

# Your Name

## Experience

### Company A — Role Title
- Built X using Y, achieving Z
- Led migration of ...

### Company B — Role Title
- Shipped feature that ...

## Skills

JavaScript, TypeScript, Node.js, React, PostgreSQL

Parsing rules #

• Sections detected by ## Heading (H2)
• Bullets under ## Experience (including ### subheadings) are extracted
• Skills from ## Skills section or comma-separated line
• highlights and skills in profile.yml override parser output when set

Cache #

Parsed output is cached at data/cache/resume-parsed.json for speed.

JD tailoring

Job description tailoring #

For each job, Raven extracts keywords from the title and matches your resume bullets to produce tailored application content.

Output columns #

Column	Meaning
jd_keywords	Terms extracted from job title (e.g. backend, python, remote)
action_words	Suggested verbs for this role type
tailored_bullets	Top resume bullets ranked by relevance to the JD

How matching works #

1. Keyword extraction — splits title on common separators, filters stop words
2. Bullet scoring — each resume bullet scored by keyword overlap with title
3. Action words — role-type heuristics (backend → “architected”, “scaled”; ML → “trained”, “deployed”)
4. Top N — resume.max_bullets from profile (default 5)

Example #

Job title: Senior Backend Engineer — Node.js

ATS form guides

ATS form guides #

When a job’s apply URL points to an ATS (Greenhouse, Lever, Ashby, Workday, etc.), Raven generates a form application guide instead of an email.

Application types #

Type	Detected when	Raven output
email	Direct email outreach possible	Subject + body
form	Apply URL on known ATS domain	Step-by-step form_steps

Form rows are not sent via raven send. Open the markdown review or CSV form_steps column and follow the guide in your browser.

Gemini plugin

Gemini draft plugin #

Optional AI polish for email drafts via Google’s Gemini API.

Setup #

1. Get an API key from Google AI Studio
2. Add to .env:

GEMINI_API_KEY=your_key_here

3. Enable in profile (optional):

draft:
  gemini:
    enabled: true
    model: "gemini-2.0-flash"

Usage #

raven draft --input data/jobs.json --gemini --max 10

Or one-shot discover + draft:

raven draft --q "backend engineer" --gemini --max 5

What Gemini does #

• Rewrites email subject and body for clarity and tone
• Preserves factual content from your resume bullets
• Does not fabricate experience — works from parsed resume + JD keywords

What Gemini does not do #

• Form application guides (ATS rows stay template-based)
• Verify email addresses
• Auto-send — you must review and run raven send yourself

Disclaimer #

Every draft includes:

What you get #

Key CSV columns #

Quick start #

./raven discover --q "backend engineer" --since 7
./raven draft --max 25
open drafts/outreach-*.md

Optional: add GEMINI_API_KEY to .env and pass --gemini for AI-polished email drafts.

Important: Review every draft yourself. Form rows are not sent via raven send.

Start with Resume parsing →