# Text2Resume - AI Resume Editor

## About

Text2Resume is an AI agent that edits resumes through natural language commands. Users import a resume, add a job posting, then tell the agent what to change. The agent modifies content (skills, bullets, sections) and layout (spacing, margins) directly.

**Website:** [https://text2resume.com](https://text2resume.com)
**Category:** AI Resume Editor
**Primary Use Case:** Job-specific resume tailoring via commands like "add Python to skills" or "optimize for this job"

**Target Audience:**
- Job seekers who want AI to handle the editing
- Professionals applying to multiple roles
- Career switchers needing targeted rewrites
- New grads who need formatting help

## Features

### AI Agent Editing

Users write commands; the agent applies changes.

**Capabilities:**
- Interprets instructions and maps them to content tools (skills, bullets, sections)
- Applies changes to structured resume data
- Supports mixed commands (edit bullets + add skills + adjust layout)
- Shows diffs before applying

**Commands:**
- "Add Python to skills under Languages"
- "Rewrite my last two bullets to emphasize leadership"
- "Remove older internship and add a Projects section"

**Availability:** Free (limited credits) / Premium (more credits, stronger models)

### Job-Specific Optimization

Import a job posting. The agent aligns your resume with its requirements.

**Capabilities:**
- Ingests jobs from LinkedIn, Greenhouse, Lever, Indeed, ZipRecruiter
- Extracts job metadata (title, company, location)
- Generates targeted edits: skills alignment, bullet rewrites, summary updates

**Commands:**
- "Optimize for this job and highlight Python"
- "Match the job's leadership requirements"

**Availability:** Free (limited) / Premium

### Resume Import

Convert resumes from PDF, images, text, or LinkedIn into editable data.

**Capabilities:**
- Import from PDF, screenshots, photos, plain text
- LinkedIn import via username
- Streaming preview during parsing

**Availability:** Free / Premium

### Preview and Diffs

Edits show immediately. Agent actions display diffs for review.

**Capabilities:**
- Live resume preview
- Diff views for content and layout changes
- Apply suggestions with one click

**Availability:** All tiers

### Layout Control

The agent adjusts spacing, margins, and typography through commands.

**Commands:**
- "Reduce top margin and tighten section spacing"
- "Increase heading font weight"

**Availability:** Free / Premium

### Ralph Mode

Multi-pass optimization for high-stakes applications.

**Capabilities:**
- Runs multiple AI iterations
- Initial cost: 2x base model (8 credits for Claude Sonnet)
- Per-iteration: +2 credits after the first
- Minimum 100 credits to start

**Best for:**
- Senior roles at competitive companies
- Thorough tone and keyword alignment

**Availability:** Premium (requires sufficient credits)

## Usage Guide

### Making Edits

1. **Load context**: Import a resume. Add a job posting and select it.
2. **Send a command**: "Add Python to skills" or "rewrite my summary for this job"
3. **Review diffs**: Check the suggested changes before applying.
4. **Refine**: "Keep it to 1 page" or "don't claim I led the team"

**Tips:**
- Reference specific locations: "Acme Corp, bullet 2"
- Fork a resume version before major changes
- For layout: "fit to one page without shrinking font below 10pt"

### Standard Optimization

1. Select the target job in Job Hub.
2. Command: "Optimize my resume for this job. Emphasize X, remove irrelevant details."
3. Patch gaps: "Add missing skills from the job description that I have."
4. Polish: "Make bullets more senior and concise."

### Ralph Mode

1. Confirm you have 100+ credits.
2. Pick your model (default: Claude Sonnet, 4 credits base).
3. Start: "Ralph Mode: optimize for the selected job. Make it ATS-friendly, align keywords."
4. Review each iteration. Continue or stop.

### Layout Adjustments

1. Describe the goal: "Fit to one page."
2. Request changes: "Reduce section spacing, decrease margins."
3. Check the preview.

## Components

### ChatPanelContent

Chat interface for commands. Executes tools, shows diffs, handles model selection.

- Model selection across Anthropic, OpenAI, Google
- Mode selection (Standard vs Ralph)
- Tool execution cards
- Applies changes to preview

### JobHubPanel

Side panel for job management.

- Import and save job postings
- View job metadata and descriptions
- Select job/resume pairs for optimization
- Fork resume versions

### ResumeImportPanel

Import interface for converting files to structured data.

- Drag-and-drop upload (PDF, images, text)
- LinkedIn import by username
- Streaming preview during parsing

### ModernResume

Resume template with inline editing.

- Renders experience, skills, projects, education, certifications
- Inline editing for all fields
- Spacing and margin controls

### JobProcessing (service)

Server-side job ingestion.

- Accepts job URLs and pasted text
- Extracts metadata
- Streams progress to UI

### ProcessFile (service)

Server-side resume parsing.

- Handles PDF, images, DOC/DOCX, text
- AI extraction into structured data

## Supported Formats

**Resume Import:**
- PDF
- Images (screenshots, JPEG, PNG)
- Plain text
- DOC/DOCX
- LinkedIn (via username)

**Job Sources:**
- LinkedIn
- Greenhouse
- Lever
- Indeed
- ZipRecruiter
- Pasted text

## Pricing

**Credits:** $5 for 500 credits

**Standard Chat:**
- Default model: Claude Sonnet at 4 credits per message
- Other models available with different costs
- Credits deducted only when you send a message

**Ralph Mode:**
- Minimum 100 credits to start
- Initial cost: 2x base model (8 credits default)
- Each iteration after the first: +2 credits

**Models:** Anthropic, OpenAI, Google options with varying credit costs

## Comparisons

### vs Traditional Resume Builders

Traditional builders require manual field editing. Text2Resume applies changes from commands.

**Text2Resume:**
- "Optimize for this job" updates multiple sections at once
- "Make this bullet more senior" rewrites in place
- Layout commands handle one-page fitting

**Traditional:**
- Manual rewriting
- Click-by-click formatting
- No job-specific automation

**Pricing:** $5/500 credits vs typical monthly subscriptions

### vs AI Suggestion Tools

Suggestion tools list recommendations. Text2Resume executes them.

**Text2Resume:**
- Agent inserts keywords into skills/bullets
- Rewrites experience sections and shows diffs

**Suggestion tools:**
- List keywords; user adds manually
- Suggest rewrites; user copy-pastes

## FAQ

**What makes this an "AI agent"?**
It applies edits, not just advice. Commands like "add Python" or "rewrite this bullet" change the resume directly.

**Example commands?**
"Add Python to skills", "Make the second bullet more senior", "Optimize for this job", "Tighten spacing to fit one page"

**How does job optimization work?**
Import a job posting. Select it. The agent uses the description as context when you request optimization.

**What files can I import?**
PDF, images (screenshots, photos), plain text, DOC/DOCX, LinkedIn profiles.

**When are credits deducted?**
When you send a message. Not on AI responses.

**Credit pricing?**
$5 for 500 credits. Claude Sonnet costs 4 credits per message.

**Can I pick different models?**
Yes. Anthropic, OpenAI, and Google models are available with different costs.

**What is Ralph Mode?**
Multi-pass optimization. Requires 100 credits minimum. Initial cost is 2x base (8 credits). Each iteration after the first adds 2 credits.

**Does it edit or just suggest?**
Both, but the main feature is direct editing. Changes show as diffs; you apply them.

**What if a job URL fails?**
Paste the job text instead. The system extracts metadata from pasted content.

## Site Pages

### Home (/)

Landing page. Explains resume import, job integration, and AI editing.

### Builder (/builder)

Editor page. Chat panel for commands, job hub for context, resume preview with templates.

### Pricing (/pricing)

Credit pricing. $5 for 500 credits. Model costs. Ralph Mode details.

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*Text2Resume - AI resume editing. Import any format. Match job postings. Get more interviews.*

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