claw-apply

Automated job search and application engine for LinkedIn and Wellfound. Searches for matching roles, applies automatically, and learns from every unknown question it encounters.

Built for OpenClaw but runs standalone with Node.js.

What it does

• Searches LinkedIn and Wellfound on a schedule with your configured keywords and filters
• Applies to matching jobs automatically via LinkedIn Easy Apply and Wellfound's native flow
• Learns — when it hits a question it can't answer, it messages you on Telegram, saves your reply, and never asks again
• Deduplicates across runs so you never apply to the same job twice
• Retries failed applications up to a configurable number of times before giving up

Quick start

git clone https://github.com/MattJackson/claw-apply.git
cd claw-apply
npm install

1. Configure

Copy the example configs and fill in your values:

cp config/settings.example.json config/settings.json
cp config/profile.example.json config/profile.json
cp config/search_config.example.json config/search_config.json

File	What to fill in
profile.json	Name, email, phone, resume path, work authorization, salary
search_config.json	Job titles, keywords, platforms, filters, exclusions
settings.json	Telegram bot token + user ID, Kernel profiles, proxy ID

2. Set up Kernel (stealth browsers)

claw-apply uses Kernel for stealth browser sessions that bypass bot detection.

npm install -g @onkernel/cli

# Create a residential proxy
kernel proxies create --type residential --country US --name "claw-apply-proxy"

# Create authenticated browser profiles (follow prompts to log in)
kernel auth create --name "LinkedIn-YourName"
kernel auth create --name "WellFound-YourName"

Add the profile names and proxy ID to config/settings.json.

3. Set up Telegram notifications

1. Message @BotFather on Telegram to create a bot
2. Copy the bot token to settings.json -> notifications.bot_token
3. Message @userinfobot to get your user ID
4. Add it to settings.json -> notifications.telegram_user_id

4. Verify setup

KERNEL_API_KEY=your_key node setup.mjs

This validates your config, tests LinkedIn and Wellfound logins, and sends a test Telegram message.

5. Run

# Search for jobs
KERNEL_API_KEY=your_key node job_searcher.mjs

# Preview what's in the queue before applying
KERNEL_API_KEY=your_key node job_applier.mjs --preview

# Apply to queued jobs
KERNEL_API_KEY=your_key node job_applier.mjs

For automated runs, set up cron or use OpenClaw's scheduler:

Search: 0 * * * *       (hourly)
Apply:  0 */6 * * *     (every 6 hours)

How it works

Search flow

1. Runs your configured keyword searches on LinkedIn and Wellfound
2. Paginates through results (LinkedIn) and infinite-scrolls (Wellfound)
3. Filters out excluded keywords and companies
4. Deduplicates against the existing queue by job ID and URL
5. Saves new jobs to data/jobs_queue.json with status new
6. Sends a Telegram summary

Apply flow

1. Picks up all new and needs_answer jobs from the queue (up to max_applications_per_run)
2. Opens a stealth browser session per platform
3. For each job:
   • LinkedIn Easy Apply: navigates to job, clicks Easy Apply, fills the multi-step modal, submits
   • Wellfound: navigates to job, clicks Apply, fills the form, submits
   • Detects and skips recruiter-only listings, external ATS jobs, and honeypot questions
4. On unknown required fields, messages you on Telegram and moves on
5. Failed jobs are retried on the next run (up to max_retries, default 2)
6. Sends a summary with counts: applied, failed, needs answer, skipped

Self-learning answers

When the applier encounters a form question it doesn't know how to answer:

1. Marks the job as needs_answer with the question text
2. Sends you a Telegram message with the question
3. You reply with the answer
4. The answer is saved to config/answers.json as a pattern match
5. Next run, it retries the job and fills in the answer automatically

Patterns support regex:

[
  { "pattern": "quota attainment", "answer": "1.12" },
  { "pattern": "years.*enterprise", "answer": "5" },
  { "pattern": "1.*10.*scale", "answer": "9" }
]

Configuration

Settings

Key	Default	Description
max_applications_per_run	no limit	Cap applications per run (optional, set to avoid rate limits)
max_retries	2	Times to retry a failed application before marking it permanently failed
browser.provider	"kernel"	"kernel" for stealth browsers, "local" for local Playwright

Search filters

Filter	Type	Description
remote	boolean	Remote jobs only
posted_within_days	number	Only jobs posted within N days
easy_apply_only	boolean	LinkedIn Easy Apply only
exclude_keywords	string[]	Skip jobs with these words in title or company
first_run_days	number	On first run, look back N days (default 90)

Project structure

claw-apply/
├── job_searcher.mjs           Search agent
├── job_applier.mjs            Apply agent
├── setup.mjs                  Setup wizard
├── status.mjs                 Queue status report
├── lib/
│   ├── constants.mjs          Shared constants and defaults
│   ├── browser.mjs            Kernel/Playwright browser factory
│   ├── session.mjs            Kernel Managed Auth session refresh
│   ├── form_filler.mjs        Generic form filling with pattern matching
│   ├── keywords.mjs           AI-generated search keywords via Claude
│   ├── linkedin.mjs           LinkedIn search + job classification
│   ├── wellfound.mjs          Wellfound search
│   ├── queue.mjs              Job queue and config management
│   ├── lock.mjs               Process lock to prevent parallel runs
│   ├── notify.mjs             Telegram notifications with rate limiting
│   └── apply/
│       ├── index.mjs          Apply handler registry
│       ├── easy_apply.mjs     LinkedIn Easy Apply
│       ├── wellfound.mjs      Wellfound apply
│       ├── greenhouse.mjs     Greenhouse ATS (stub)
│       ├── lever.mjs          Lever ATS (stub)
│       ├── workday.mjs        Workday ATS (stub)
│       ├── ashby.mjs          Ashby ATS (stub)
│       └── jobvite.mjs        Jobvite ATS (stub)
├── config/
│   ├── *.example.json         Templates (committed)
│   ├── profile.json           Your info (gitignored)
│   ├── search_config.json     Your searches (gitignored)
│   ├── answers.json           Learned answers (gitignored)
│   └── settings.json          Your settings (gitignored)
└── data/
    ├── jobs_queue.json         Job queue (auto-managed)
    └── applications_log.json   Application history (auto-managed)

Job statuses

Status	Meaning
new	Found, waiting to apply
applied	Successfully submitted
needs_answer	Blocked on unknown question, waiting for your reply
failed	Failed after max retries
already_applied	Duplicate detected, previously applied
skipped_honeypot	Honeypot question detected
skipped_recruiter_only	LinkedIn recruiter-only listing
skipped_external_unsupported	External ATS (Greenhouse, Lever, etc. — stubs ready)
skipped_easy_apply_unsupported	LinkedIn job without Easy Apply button
skipped_no_apply	No apply button, modal, or submit found on page
stuck	Modal progress stalled
incomplete	Ran out of modal steps without submitting

Roadmap

• LinkedIn Easy Apply
• Wellfound apply
• Kernel stealth browsers + residential proxy
• Self-learning answer bank
• Retry logic for transient failures
• Preview mode (--preview)
• Configurable application caps and retry limits
• Indeed support
• External ATS support (Greenhouse, Lever, Workday, Ashby, Jobvite — stubs ready)
• Job scoring and ranking
• Per-job cover letter generation via LLM

License

AGPL-3.0-or-later