--- name: linkedin-autopilot description: Your agent builds your LinkedIn presence while you sleep. Schedule posts, auto-engage with target accounts, run personalized DM sequences, and never miss an engagement opportunity. Handles connection requests, profile visiting campaigns, post engagement, and follow-up sequences with safety throttling and human-like behavior patterns. Configure your targets, define engagement rules, and let your agent network 24/7. Use when setting up LinkedIn automation, managing posting schedules, running engagement campaigns, or building agent-driven LinkedIn lead generation workflows. metadata: clawdbot: emoji: "🤝" requires: browser: true env: - LINKEDIN_EMAIL - LINKEDIN_PASSWORD ---

LinkedIn Autopilot — Your Agent Networks 24/7

You sleep. Your LinkedIn thrives.

LinkedIn Autopilot turns your agent into a 24/7 LinkedIn manager. It schedules posts, auto-engages with target accounts, runs personalized DM sequences, and builds your network while you focus on actual work. No more "I should post more" guilt. No more missing engagement windows. No more manual connection request grinding.

What makes it different: This isn't a dumb bot — it's your agent using real browser automation with human-like behavior patterns. Random delays, natural engagement patterns, safety throttling, and intelligent targeting. Multi-day sequences with conditional logic. State tracking across sessions. Full reporting on what worked.

The Pain Points This Solves

❌ "I spend 2 hours/day on LinkedIn and have nothing to show for it" ✅ Your agent handles engagement, DMs, and connection building automatically

❌ "I post inconsistently and my reach is dying" ✅ Scheduled posts with optimal timing — your agent never forgets

❌ "I see opportunities to engage but I'm too busy" ✅ Auto-engage on target accounts' posts with personalized comments

❌ "Follow-up sequences are tedious and I drop leads" ✅ Multi-step DM sequences with conditional logic — your agent follows up

❌ "I want to build my network but connection requests feel spammy" ✅ Targeted connection campaigns with personalized notes and safety limits

Setup

1. Run scripts/setup.sh to initialize config and data directories
2. Edit ~/.config/linkedin-autopilot/config.json with targets, sequences, and posting schedule
3. Store LinkedIn credentials in ~/.clawdbot/secrets.env:

```bash [email protected] LINKEDIN_PASSWORD=your-password ```

1. Test with: scripts/engage.sh --dry-run

Config

Config lives at ~/.config/linkedin-autopilot/config.json. See config.example.json for full schema.

Key sections:

• identity — Your LinkedIn profile info (for personalization)
• targets — Who/what to engage with (companies, people, keywords)
• posting — Schedule, content queue, optimal times
• engagement — Auto-like/comment rules, target post patterns
• outreach — Connection request campaigns, DM sequences
• safety — Rate limits, delays, warmup period, blackout windows

Scripts

| Script | Purpose | |--------|---------| | scripts/setup.sh | Initialize config and data directories | | scripts/post.sh | Post scheduled content from queue | | scripts/engage.sh | Auto-engage on target posts (like, comment, share) | | scripts/dm-sequence.sh | Manage DM sequences (send, follow-up, track) | | scripts/connect.sh | Send connection requests to target profiles | | scripts/report.sh | Generate analytics report (engagement, growth, conversions) |

All scripts support --dry-run for testing without actually posting/engaging.

Posting Workflow

Run scripts/post.sh on schedule (cron daily at optimal times). The script:

1. Checks posting queue in config
2. Verifies timing (respects blackout windows, rate limits)
3. Logs into LinkedIn via browser automation
4. Posts content with configured formatting
5. Tracks post performance
6. Updates queue state

Post queue example:

"posts": [
  {
    "content": "5 lessons from building AI agents in production:\n\n1. ...",
    "scheduled_time": "2024-01-28T09:00:00Z",
    "status": "pending",
    "media": null
  }
]

Engagement Workflow

Run scripts/engage.sh 3-4x daily. The script:

1. Searches for posts matching target criteria (keywords, accounts, hashtags)
2. Scores relevance (content match, author influence, engagement level)
3. Engages with top posts (like, thoughtful comment, or share)
4. Tracks engagement to avoid repeats
5. Respects rate limits (20-30 engagements per run)

Target patterns:

• Posts from specific companies/people
• Posts with keywords/hashtags
• Posts in your feed from connections
• Trending posts in your industry

Engagement types:

• Like: Quick signal, low friction
• Comment: Generated from templates + post context (not spammy)
• Share: With your take/commentary added

DM Sequence Workflow

Run scripts/dm-sequence.sh daily. The script:

1. Checks active sequences for people at each stage
2. Sends next message in sequence (respects delays)
3. Detects replies and advances/pauses accordingly
4. Handles conditional branching (replied vs not replied)
5. Reports on conversion rates

Sequence example:

{
  "name": "consulting-intro",
  "trigger": "new_connection",
  "steps": [
    {
      "delay_hours": 24,
      "message": "Hey {first_name}! Thanks for connecting. I help {title}s with {pain_point}. Are you currently working on anything in this space?",
      "condition": null
    },
    {
      "delay_hours": 72,
      "message": "Following up — I saw your post about {topic}. Would love to chat about {offering}. Free for a quick call this week?",
      "condition": "no_reply"
    }
  ]
}

Connection Request Workflow

Run scripts/connect.sh weekly (not daily — LinkedIn limits this). The script:

1. Searches for target profiles (job titles, companies, keywords)
2. Filters out existing connections and pending requests
3. Generates personalized connection notes
4. Sends requests with safety throttling (20-30/week max)
5. Tracks acceptance rate

Target criteria:

"connection_targets": [
  {
    "query": "AI consultant OR automation specialist",
    "companies": ["Microsoft", "Google", "OpenAI"],
    "exclude_titles": ["Recruiter"],
    "note_template": "Hey {first_name}, I'm building AI tools for {industry} and saw your work at {company}. Would love to connect!"
  }
]

Safety & Rate Limits

LinkedIn Autopilot follows conservative rate limits to avoid account flags:

| Action | Limit | Timing | |--------|-------|--------| | Posts | 1-2/day | Optimal hours (9am-11am, 2pm-4pm) | | Engagements | 80-100/day | Spread across 3-4 runs | | Connection Requests | 20-30/week | Gradual warmup over first 2 weeks | | DMs | 30-50/day | Random delays 5-15min between sends | | Profile Views | 50-80/day | Natural browsing pattern |

Warmup Period: First 2 weeks run at 50% capacity to establish normal behavior pattern.

Blackout Windows: No activity during nights/weekends (configurable).

Random Delays: 3-8 seconds between actions, 5-15 minutes between campaigns.

Human-Like Patterns: Varied engagement times, occasional skips, natural language variance.

State Tracking

All activity is logged and tracked:

~/.config/linkedin-autopilot/
├── config.json              # User configuration
├── posts-queue.json         # Scheduled posts
├── engagement-history.json  # Posts engaged with (dedup)
├── dm-sequences.json        # Active DM threads
├── connections.json         # Connection requests + status
├── analytics.json           # Performance metrics
└── activity-log.json        # Full audit trail

Reporting

scripts/report.sh generates performance reports:

...