- Add Telegram answer learning flow (poller + applier safety net) - Add AI filtering, job scoring, cross-track dedup - Add browser crash recovery, fuzzy select matching, shadow DOM details - Update file structure with all new modules - Update job statuses (no_modal, stuck, filtered, duplicate) - Update scheduling info (OpenClaw crons, not crontab/PM2) - Update roadmap Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
8.6 KiB
name, description
| name | description |
|---|---|
| claw-apply | Automated job search and application for LinkedIn and Wellfound. Searches for matching roles every 12 hours, AI-filters and scores them, applies automatically using Playwright + Kernel stealth browsers. Handles LinkedIn Easy Apply multi-step modals and Wellfound applications. Self-learning — asks you via Telegram when it hits an unknown question, suggests an AI answer, saves your reply, and never asks again. Recovers from browser crashes and retries failed applications automatically. |
claw-apply
Automated job search and application. Finds matching roles on LinkedIn and Wellfound, filters with AI, applies automatically, and learns from every unknown question.
Requirements
- Node.js 18+
- Kernel account — stealth browsers + bot detection bypass (required)
- Kernel CLI:
npm install -g @onkernel/cli— see kernel/skills for CLI + auth guidance - Telegram bot for notifications and interactive Q&A (BotFather)
- Anthropic API key (optional — enables AI filtering, keyword generation, and suggested answers)
- OpenClaw (optional — enables auto-scheduling via crons)
Note: Playwright is installed automatically via
npm installas a library for browser connectivity. You don't need to install it globally or manage browsers yourself — Kernel handles all browser execution.
Setup
1. Install
git clone https://github.com/MattJackson/claw-apply.git
cd claw-apply
npm install
2. Kernel: proxy + auth sessions
# Log in to Kernel
kernel login
# Create a residential proxy (US recommended for LinkedIn/Wellfound)
kernel proxies create --type residential --country US --name "claw-apply-proxy"
# Note the proxy ID from output
# Create managed auth connections (one per platform)
kernel auth connections create --profile-name "LinkedIn-YourName" --domain linkedin.com
# Note the connection ID from output
kernel auth connections create --profile-name "WellFound-YourName" --domain wellfound.com
# Note the connection ID from output
# Trigger initial login flows (opens a browser URL to complete auth)
kernel auth connections login <linkedin-connection-id>
kernel auth connections login <wellfound-connection-id>
3. Configure
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
settings.json — fill in:
notifications.telegram_user_id— your Telegram user IDnotifications.bot_token— Telegram bot token from BotFatherkernel.proxy_id— proxy ID from step 2kernel.profiles.linkedin— profile name e.g.LinkedIn-YourNamekernel.profiles.wellfound— profile name e.g.WellFound-YourNamekernel.connection_ids.linkedin— connection ID from step 2kernel.connection_ids.wellfound— connection ID from step 2
profile.json — your name, email, phone, resume path, work authorization, salary targets
search_config.json — keywords, platforms, location filters, salary filters, exclusions
4. Create .env
Create a .env file in the project root (gitignored — never commit this):
KERNEL_API_KEY=your_kernel_api_key
ANTHROPIC_API_KEY=your_anthropic_api_key # optional, for AI features
5. Verify
node setup.mjs
Setup will:
- Validate all config files
- Write
.env(mode 600) if API keys are set - Send a Telegram test message
- Test LinkedIn + Wellfound logins
6. Schedule with OpenClaw crons
Scheduling is managed via OpenClaw cron jobs (not system crontab):
| Job | Schedule | Description |
|---|---|---|
| Searcher | 0 */12 * * * America/Los_Angeles |
Search every 12 hours |
| Filter | 30 * * * * America/Los_Angeles |
AI filter every hour at :30 |
| Applier | disabled by default | Enable when ready to auto-apply |
| Telegram Poller | * * * * * America/Los_Angeles |
Process answer replies every minute |
The lockfile mechanism ensures only one instance of each agent runs at a time.
7. Run manually
node job_searcher.mjs # search now
node job_filter.mjs # AI filter + score jobs
node job_applier.mjs --preview # preview queue without applying
node job_applier.mjs # apply now
node telegram_poller.mjs # process Telegram answer replies
node status.mjs # show queue + run status
How it works
Search — runs your keyword searches on LinkedIn and Wellfound, paginates through results, classifies each job (Easy Apply vs external ATS), filters exclusions, deduplicates, and queues new jobs. First run searches 90 days back; subsequent runs search 2 days.
Filter — submits jobs to Claude AI via Anthropic Batch API for scoring (1-10). Jobs below the threshold are filtered out. Cross-track deduplication keeps the highest-scoring copy. Two-phase design for cron compatibility.
Apply — picks up queued jobs sorted by priority (Easy Apply first), opens stealth browser sessions, fills forms using your profile + learned answers, and submits. Processes Telegram replies at start of each run. Reloads answers.json before each job. Auto-recovers from browser crashes. Retries failed jobs (default 2 retries). Per-job timeout of 10 minutes.
Learn — on unknown questions, Claude suggests an answer and you're messaged on Telegram. Reply with your answer or "ACCEPT" the AI suggestion. The Telegram poller saves it to answers.json instantly and the job is retried next run. Over time, all questions get answered and the system runs fully autonomously.
Lockfile — prevents parallel runs. If an agent is already running, a second invocation exits immediately.
File structure
claw-apply/
├── job_searcher.mjs Search agent
├── job_filter.mjs AI filter + scoring agent
├── job_applier.mjs Apply agent
├── telegram_poller.mjs Telegram answer reply processor
├── setup.mjs Setup wizard
├── status.mjs Queue + run status report
├── lib/
│ ├── browser.mjs Kernel stealth browser factory
│ ├── session.mjs Auth session refresh via Kernel API
│ ├── env.mjs .env loader
│ ├── linkedin.mjs LinkedIn search + job classification
│ ├── wellfound.mjs Wellfound search + apply
│ ├── form_filler.mjs Form filling with pattern matching
│ ├── ai_answer.mjs AI answer generation via Claude
│ ├── filter.mjs AI job scoring via Anthropic Batch API
│ ├── keywords.mjs AI-enhanced keyword generation
│ ├── queue.mjs Job queue with atomic writes
│ ├── lock.mjs PID lockfile + graceful shutdown
│ ├── notify.mjs Telegram Bot API (send, getUpdates, reply)
│ ├── telegram_answers.mjs Telegram reply → answers.json processing
│ ├── search_progress.mjs Per-platform search resume tracking
│ ├── constants.mjs Shared constants + ATS patterns
│ └── apply/
│ ├── index.mjs Handler registry + status normalization
│ ├── easy_apply.mjs LinkedIn Easy Apply (full)
│ ├── wellfound.mjs Wellfound apply (full)
│ ├── greenhouse.mjs Greenhouse (stub)
│ ├── lever.mjs Lever (stub)
│ ├── workday.mjs Workday (stub)
│ ├── ashby.mjs Ashby (stub)
│ └── jobvite.mjs Jobvite (stub)
├── config/
│ ├── *.example.json Templates (committed)
│ └── *.json Your config (gitignored)
└── data/ Runtime data (gitignored, auto-managed)
answers.json — self-learning Q&A
When the applier can't answer a question, it asks Claude for a suggestion and messages you on Telegram. Your reply is saved and reused forever:
[
{ "pattern": "quota attainment", "answer": "1.12" },
{ "pattern": "years.*enterprise", "answer": "5" },
{ "pattern": "1.*10.*scale", "answer": "9" }
]
Patterns are matched case-insensitively and support regex. First match wins.
ATS support
| Platform | Status |
|---|---|
| LinkedIn Easy Apply | Full |
| Wellfound | Full |
| Greenhouse | Stub |
| Lever | Stub |
| Workday | Stub |
| Ashby | Stub |
| Jobvite | Stub |
External ATS jobs are queued and classified — stubs will be promoted to full implementations based on usage data.