AI Agents CLIClawHub Skill

Resume CLI for AI Agents

Generate, tailor, and parse professional PDF resumes and cover letters from the command line. Built for AI agents like OpenClaw and Claude Code to create job-ready documents.

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ClawHubopenclaw skills install useresume

npmnpm install -g @useresume/cli

Read the full API docs

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useresume — terminal

$ useresume credentials:test

{ "success": true, "data": { "api_credits": 96, "expires_at": null } }

$ useresume resume:create --input resume.json

{ "success": true, "data": { "file_url": "https://..." } }

$ useresume resume:create-tailored --input tailored.json

{ "success": true, "meta": { "credits_used": 5 } }

$ useresume resume:parse --file ./cv.pdf --parse-to json

{ "success": true, "data": { "name": "Jane Doe", ... } }

Get started in seconds

Choose the install path that fits your workflow: ClawHub for OpenClaw, or npm for any shell-capable agent.

terminal

# Install the published OpenClaw skill

$ openclaw skills install useresume

# Or install the CLI directly

$ npm install -g @useresume/cli

# Set your API key

$ export USERESUME_API_KEY=ur_your_key_here

# Verify your credentials

$ useresume credentials:test

{ "success": true, "data": { "api_credits": 30, "expires_at": null } }

# Generate your first resume

$ useresume resume:create --input resume.json

{ "success": true, "data": { "file_url": "https://..." }, "meta": { "credits_used": 1 } }

ClawHub listing npm package API key dashboard

Built for automation

Every design decision prioritizes machine readability. JSON in, JSON out, non-zero exit codes on failure.

AI Agent Ready

Every command outputs structured JSON to stdout. Agents parse the response directly — no scraping, no regex, no surprises.

Structured JSON I/O

Input via JSON files, output via JSON stdout. Errors, success, and metadata all follow the same contract agents can rely on.

Resume + Cover Letter

Generate resumes, cover letters, and tailored versions of both. Parse existing documents into structured data or markdown.

29 Templates, 32 Colors

Choose from 29 resume templates, 11 cover letter templates, 32 accent colors, 9 fonts, and 16 background colors.

Multi-Language Support

Generate documents in 9 languages: English, Spanish, French, German, Italian, Portuguese, Dutch, Polish, and Lithuanian.

Fast PDF Generation

Resumes render in 1-2 seconds. Tailored versions use AI to optimize content for a specific job description.

Command reference

Eight commands cover the full document lifecycle: create, tailor, parse, and monitor.

Command	Description	Credits
`resume:create`	Generate a professional PDF resume from JSON input	1
`resume:create-tailored`	AI-tailored resume optimized for a specific job description	5
`resume:parse`	Parse an existing resume file into structured JSON or markdown	4
`cover-letter:create`	Generate a PDF cover letter from JSON input	1
`cover-letter:create-tailored`	AI-tailored cover letter optimized for a specific job description	5
`cover-letter:parse`	Parse an existing cover letter into structured JSON or markdown	4
`run:get`	Check the status of an async run by its ID	0
`credentials:test`	Test API key validity and check remaining credits	0

How agents use it

A typical end-to-end workflow: find a job, build the resume, tailor it with AI, download the PDF, and apply.

1

Find a job & grab the description

The agent discovers a role the candidate wants to apply for and extracts the job description text.

# Agent scrapes or receives the job posting

{ "title": "Senior Engineer", "company": "Acme", "description": "We are looking for..." }

2

Build the resume JSON

Structure the candidate's experience, skills, and education into the UseResume JSON schema — or parse an existing PDF.

$ useresume resume:parse --file ./cv.pdf --parse-to json

{ "success": true, "data": { "name": "Jane Doe", "experience": [...] } }

3

Tailor to the job description

Pass the resume data and job description to the AI. It rewrites bullet points, reorders skills, and optimizes for ATS.

$ useresume resume:create-tailored --input tailored.json

{ "success": true, "data": { "file_url": "https://cdn..." } }

4

Download the PDF & apply

Grab the PDF from the returned URL and submit the application. The agent can also generate a matching cover letter in the same flow.

# Download the tailored resume

$ curl -o resume.pdf "$FILE_URL"

# Optionally generate a cover letter too

$ useresume cover-letter:create-tailored --input cl.json

Built for OpenClaw

The published ClawHub skill gives OpenClaw the install path, runtime requirements, and command contract it needs to use UseResume safely.

Skill-based discovery

After the skill is installed, OpenClaw reads the bundledSKILL.mdmetadata, checks the required environment variables and binary, and loads the recommended workflows for resume generation, tailoring, parsing, and run checks.

Published on ClawHub as the useresume skill
Install with openclaw skills install useresume
SKILL.md declares USERESUME_API_KEY and the useresume binary
Install metadata points to @useresume/cli on npm
All commands return JSON to stdout with non-zero exits on failure
Best experience in OpenClaw, usable anywhere shell commands + JSON are supported

SKILL.md

---

name: useresume

description: Generate professional PDF resumes...

metadata: {"openclaw":{"requires":{"env":

["USERESUME_API_KEY"],"bins":

["useresume"]},...}}

---

# Install rules, commands,

# schemas, workflows...

Common questions

Quick answers for developers and agent builders integrating the UseResume CLI.

What is the UseResume CLI?

The UseResume CLI (@useresume/cli) is a command-line tool that wraps the UseResume API. It lets AI agents like OpenClaw, Claude Code, and custom automation scripts generate, tailor, and parse professional PDF resumes and cover letters — all with structured JSON output.

How do OpenClaw agents discover this skill?

Install the published skill with openclaw skills install useresume. After that, OpenClaw reads the bundled SKILL.md to understand the command set, required environment variables, and recommended workflows.

Does the CLI work with Claude Code and other agents?

Yes. Any coding agent or automation runtime that can execute shell commands and parse JSON can use the CLI. OpenClaw gets the cleanest install flow via the published skill, but the npm package works anywhere shell execution is available.

How much does it cost?

You get 30 free API credits when you sign up. Creating a resume or cover letter costs 1 credit, tailoring costs 5 credits, and parsing costs 4 credits. Checking run status and testing credentials are free.

What templates and styles are available?

29 resume templates, 11 cover letter templates, 32 accent colors, 9 fonts, 16 background colors, and 9 document languages. All configurable via the JSON input file.

Can I parse an existing resume and tailor it?

Yes. Use resume:parse to extract structured data from an existing PDF, then feed that data plus a job description into resume:create-tailored. This is the most common agent workflow.

Install the skill, then let your agent do the work.

Get an API key, install useresume from ClawHub or npm, and hand resume creation, tailoring, and parsing to your OpenClaw workflow.

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