{ "schemaVersion": "1.0", "item": { "slug": "linkedin-autopilot", "name": "LinkedIn Autopilot", "source": "tencent", "type": "skill", "category": "效率提升", "sourceUrl": "https://clawhub.ai/audsmith28/linkedin-autopilot", "canonicalUrl": "https://clawhub.ai/audsmith28/linkedin-autopilot", "targetPlatform": "OpenClaw" }, "install": { "downloadMode": "redirect", "downloadUrl": "/downloads/linkedin-autopilot", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=linkedin-autopilot", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "installMethod": "Manual import", "extraction": "Extract archive", "prerequisites": [ "OpenClaw" ], "packageFormat": "ZIP package", "includedAssets": [ "SKILL.md", "config.example.json", "scripts/connect.sh", "scripts/dm-sequence.sh", "scripts/engage.sh", "scripts/post.sh" ], "primaryDoc": "SKILL.md", "quickSetup": [ "Download the package from Yavira.", "Extract the archive and review SKILL.md first.", "Import or place the package into your OpenClaw setup." ], "agentAssist": { "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.", "steps": [ "Download the package from Yavira.", "Extract it into a folder your agent can access.", "Paste one of the prompts below and point your agent at the extracted folder." ], "prompts": [ { "label": "New install", "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete." }, { "label": "Upgrade existing", "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run." } ] }, "sourceHealth": { "source": "tencent", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-04-23T16:43:11.935Z", "expiresAt": "2026-04-30T16:43:11.935Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard", "contentDisposition": "attachment; filename=\"4claw-imageboard-1.0.1.zip\"", "redirectLocation": null, "bodySnippet": null }, "scope": "source", "summary": "Source download looks usable.", "detail": "Yavira can redirect you to the upstream package for this source.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/linkedin-autopilot" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] }, "downloadPageUrl": "https://openagent3.xyz/downloads/linkedin-autopilot", "agentPageUrl": "https://openagent3.xyz/skills/linkedin-autopilot/agent", "manifestUrl": "https://openagent3.xyz/skills/linkedin-autopilot/agent.json", "briefUrl": "https://openagent3.xyz/skills/linkedin-autopilot/agent.md" }, "agentAssist": { "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.", "steps": [ "Download the package from Yavira.", "Extract it into a folder your agent can access.", "Paste one of the prompts below and point your agent at the extracted folder." ], "prompts": [ { "label": "New install", "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete." }, { "label": "Upgrade existing", "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run." } ] }, "documentation": { "source": "clawhub", "primaryDoc": "SKILL.md", "sections": [ { "title": "LinkedIn Autopilot — Your Agent Networks 24/7", "body": "You sleep. Your LinkedIn thrives.\n\nLinkedIn 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.\n\nWhat 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." }, { "title": "The Pain Points This Solves", "body": "❌ \"I spend 2 hours/day on LinkedIn and have nothing to show for it\"\n✅ Your agent handles engagement, DMs, and connection building automatically\n\n❌ \"I post inconsistently and my reach is dying\"\n✅ Scheduled posts with optimal timing — your agent never forgets\n\n❌ \"I see opportunities to engage but I'm too busy\"\n✅ Auto-engage on target accounts' posts with personalized comments\n\n❌ \"Follow-up sequences are tedious and I drop leads\"\n✅ Multi-step DM sequences with conditional logic — your agent follows up\n\n❌ \"I want to build my network but connection requests feel spammy\"\n✅ Targeted connection campaigns with personalized notes and safety limits" }, { "title": "Setup", "body": "Run scripts/setup.sh to initialize config and data directories\nEdit ~/.config/linkedin-autopilot/config.json with targets, sequences, and posting schedule\nStore LinkedIn credentials in ~/.clawdbot/secrets.env:\nLINKEDIN_EMAIL=your-email@example.com\nLINKEDIN_PASSWORD=your-password\n\n\nTest with: scripts/engage.sh --dry-run" }, { "title": "Config", "body": "Config lives at ~/.config/linkedin-autopilot/config.json. See config.example.json for full schema.\n\nKey sections:\n\nidentity — Your LinkedIn profile info (for personalization)\ntargets — Who/what to engage with (companies, people, keywords)\nposting — Schedule, content queue, optimal times\nengagement — Auto-like/comment rules, target post patterns\noutreach — Connection request campaigns, DM sequences\nsafety — Rate limits, delays, warmup period, blackout windows" }, { "title": "Scripts", "body": "ScriptPurposescripts/setup.shInitialize config and data directoriesscripts/post.shPost scheduled content from queuescripts/engage.shAuto-engage on target posts (like, comment, share)scripts/dm-sequence.shManage DM sequences (send, follow-up, track)scripts/connect.shSend connection requests to target profilesscripts/report.shGenerate analytics report (engagement, growth, conversions)\n\nAll scripts support --dry-run for testing without actually posting/engaging." }, { "title": "Posting Workflow", "body": "Run scripts/post.sh on schedule (cron daily at optimal times). The script:\n\nChecks posting queue in config\nVerifies timing (respects blackout windows, rate limits)\nLogs into LinkedIn via browser automation\nPosts content with configured formatting\nTracks post performance\nUpdates queue state\n\nPost queue example:\n\n\"posts\": [\n {\n \"content\": \"5 lessons from building AI agents in production:\\n\\n1. ...\",\n \"scheduled_time\": \"2024-01-28T09:00:00Z\",\n \"status\": \"pending\",\n \"media\": null\n }\n]" }, { "title": "Engagement Workflow", "body": "Run scripts/engage.sh 3-4x daily. The script:\n\nSearches for posts matching target criteria (keywords, accounts, hashtags)\nScores relevance (content match, author influence, engagement level)\nEngages with top posts (like, thoughtful comment, or share)\nTracks engagement to avoid repeats\nRespects rate limits (20-30 engagements per run)\n\nTarget patterns:\n\nPosts from specific companies/people\nPosts with keywords/hashtags\nPosts in your feed from connections\nTrending posts in your industry\n\nEngagement types:\n\nLike: Quick signal, low friction\nComment: Generated from templates + post context (not spammy)\nShare: With your take/commentary added" }, { "title": "DM Sequence Workflow", "body": "Run scripts/dm-sequence.sh daily. The script:\n\nChecks active sequences for people at each stage\nSends next message in sequence (respects delays)\nDetects replies and advances/pauses accordingly\nHandles conditional branching (replied vs not replied)\nReports on conversion rates\n\nSequence example:\n\n{\n \"name\": \"consulting-intro\",\n \"trigger\": \"new_connection\",\n \"steps\": [\n {\n \"delay_hours\": 24,\n \"message\": \"Hey {first_name}! Thanks for connecting. I help {title}s with {pain_point}. Are you currently working on anything in this space?\",\n \"condition\": null\n },\n {\n \"delay_hours\": 72,\n \"message\": \"Following up — I saw your post about {topic}. Would love to chat about {offering}. Free for a quick call this week?\",\n \"condition\": \"no_reply\"\n }\n ]\n}" }, { "title": "Connection Request Workflow", "body": "Run scripts/connect.sh weekly (not daily — LinkedIn limits this). The script:\n\nSearches for target profiles (job titles, companies, keywords)\nFilters out existing connections and pending requests\nGenerates personalized connection notes\nSends requests with safety throttling (20-30/week max)\nTracks acceptance rate\n\nTarget criteria:\n\n\"connection_targets\": [\n {\n \"query\": \"AI consultant OR automation specialist\",\n \"companies\": [\"Microsoft\", \"Google\", \"OpenAI\"],\n \"exclude_titles\": [\"Recruiter\"],\n \"note_template\": \"Hey {first_name}, I'm building AI tools for {industry} and saw your work at {company}. Would love to connect!\"\n }\n]" }, { "title": "Safety & Rate Limits", "body": "LinkedIn Autopilot follows conservative rate limits to avoid account flags:\n\nActionLimitTimingPosts1-2/dayOptimal hours (9am-11am, 2pm-4pm)Engagements80-100/daySpread across 3-4 runsConnection Requests20-30/weekGradual warmup over first 2 weeksDMs30-50/dayRandom delays 5-15min between sendsProfile Views50-80/dayNatural browsing pattern\n\nWarmup Period: First 2 weeks run at 50% capacity to establish normal behavior pattern.\n\nBlackout Windows: No activity during nights/weekends (configurable).\n\nRandom Delays: 3-8 seconds between actions, 5-15 minutes between campaigns.\n\nHuman-Like Patterns: Varied engagement times, occasional skips, natural language variance." }, { "title": "State Tracking", "body": "All activity is logged and tracked:\n\n~/.config/linkedin-autopilot/\n├── config.json # User configuration\n├── posts-queue.json # Scheduled posts\n├── engagement-history.json # Posts engaged with (dedup)\n├── dm-sequences.json # Active DM threads\n├── connections.json # Connection requests + status\n├── analytics.json # Performance metrics\n└── activity-log.json # Full audit trail" }, { "title": "Reporting", "body": "scripts/report.sh generates performance reports:\n\nWeekly Summary:\n\nPosts published (reach, engagement rate)\nEngagements performed (breakdown by type)\nConnection requests (sent, accepted, pending)\nDM sequences (active, replied, converted)\nGrowth metrics (followers, connections, profile views)\n\nLead Conversion Tracking:\n\nDM replies → qualified leads\nConnection acceptances → engaged conversations\nPost engagement → inbound interest" }, { "title": "1. Thought Leader Building", "body": "Post 1x/day on schedule (industry insights, lessons learned)\nAuto-engage with 20-30 posts daily from influencers in your space\nShare top posts with your commentary\nTrack which content types drive the most profile views" }, { "title": "2. Outbound Lead Gen", "body": "Connect with 20-30 target profiles weekly (ICP: CTOs at Series A startups)\nRun DM sequence on new connections (intro → value prop → call booking)\nAuto-engage with prospects' posts before sending sequence\nReport on reply rate and meeting bookings" }, { "title": "3. Network Maintenance", "body": "Like posts from existing connections (stay top of mind)\nComment thoughtfully on key accounts' updates\nShare relevant content to your feed\nPeriodic check-ins via DM (birthday, work anniversary, post milestone)" }, { "title": "LinkedIn TOS Compliance", "body": "Important: LinkedIn's ToS prohibits automation. This tool is designed for:\n\nPersonal use with human oversight (you review/approve actions)\nAgent-assisted workflows (agent suggests, human approves)\nBatch scheduling (compose in bulk, post on schedule)\n\nRecommended approach:\n\nUse --dry-run mode to preview actions\nReview queued posts/messages before enabling auto-send\nSet conservative rate limits\nMonitor for account warnings\nAlways have a human in the loop for sensitive actions\n\nThis tool is provided as-is for educational purposes. Use responsibly." }, { "title": "Data Files", "body": "~/.config/linkedin-autopilot/\n├── config.json # Main configuration\n├── posts-queue.json # Scheduled content\n├── engagement-history.json # Activity dedup\n├── dm-sequences.json # Active conversations\n├── connections.json # Network building state\n├── analytics.json # Performance tracking\n└── activity-log.json # Full audit trail" }, { "title": "Browser Automation", "body": "Uses Clawdbot's built-in browser control:\n\nSnapshot → Act → Verify pattern\nHandles login, 2FA prompts, session management\nRetries on rate limit detection\nGraceful handling of LinkedIn UI changes" }, { "title": "Advanced Features", "body": "A/B Testing: Test post variants, measure which performs better\n\nSmart Scheduling: ML-based optimal posting time suggestion\n\nReply Detection: Pauses DM sequences when prospect replies\n\nSentiment Analysis: Adjusts engagement strategy based on post sentiment\n\nNetwork Mapping: Tracks who engages with your content (potential advocates)" }, { "title": "Troubleshooting", "body": "\"LinkedIn security check triggered\"\n→ Reduce rate limits in config, extend delays, complete security verification manually\n\n\"Posts not publishing\"\n→ Check activity-log.json for errors, verify LinkedIn session still valid\n\n\"DM sequences not advancing\"\n→ Verify reply detection is working, check conversation state in dm-sequences.json\n\n\"Connection requests rejected frequently\"\n→ Improve note personalization, target better ICP matches, reduce volume" }, { "title": "Contributing", "body": "Want to add features? See references/linkedin-api.md for browser automation patterns and references/sequence-engine.md for DM workflow logic.\n\nRemember: Your agent is a force multiplier, not a replacement for authentic networking. Use it to handle the tedious parts so you can focus on the conversations that matter." } ], "body": "LinkedIn Autopilot — Your Agent Networks 24/7\n\nYou sleep. Your LinkedIn thrives.\n\nLinkedIn 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.\n\nWhat 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.\n\nThe Pain Points This Solves\n\n❌ \"I spend 2 hours/day on LinkedIn and have nothing to show for it\"\n✅ Your agent handles engagement, DMs, and connection building automatically\n\n❌ \"I post inconsistently and my reach is dying\"\n✅ Scheduled posts with optimal timing — your agent never forgets\n\n❌ \"I see opportunities to engage but I'm too busy\"\n✅ Auto-engage on target accounts' posts with personalized comments\n\n❌ \"Follow-up sequences are tedious and I drop leads\"\n✅ Multi-step DM sequences with conditional logic — your agent follows up\n\n❌ \"I want to build my network but connection requests feel spammy\"\n✅ Targeted connection campaigns with personalized notes and safety limits\n\nSetup\nRun scripts/setup.sh to initialize config and data directories\nEdit ~/.config/linkedin-autopilot/config.json with targets, sequences, and posting schedule\nStore LinkedIn credentials in ~/.clawdbot/secrets.env:\nLINKEDIN_EMAIL=your-email@example.com\nLINKEDIN_PASSWORD=your-password\n\nTest with: scripts/engage.sh --dry-run\nConfig\n\nConfig lives at ~/.config/linkedin-autopilot/config.json. See config.example.json for full schema.\n\nKey sections:\n\nidentity — Your LinkedIn profile info (for personalization)\ntargets — Who/what to engage with (companies, people, keywords)\nposting — Schedule, content queue, optimal times\nengagement — Auto-like/comment rules, target post patterns\noutreach — Connection request campaigns, DM sequences\nsafety — Rate limits, delays, warmup period, blackout windows\nScripts\nScript\tPurpose\nscripts/setup.sh\tInitialize config and data directories\nscripts/post.sh\tPost scheduled content from queue\nscripts/engage.sh\tAuto-engage on target posts (like, comment, share)\nscripts/dm-sequence.sh\tManage DM sequences (send, follow-up, track)\nscripts/connect.sh\tSend connection requests to target profiles\nscripts/report.sh\tGenerate analytics report (engagement, growth, conversions)\n\nAll scripts support --dry-run for testing without actually posting/engaging.\n\nPosting Workflow\n\nRun scripts/post.sh on schedule (cron daily at optimal times). The script:\n\nChecks posting queue in config\nVerifies timing (respects blackout windows, rate limits)\nLogs into LinkedIn via browser automation\nPosts content with configured formatting\nTracks post performance\nUpdates queue state\n\nPost queue example:\n\n\"posts\": [\n {\n \"content\": \"5 lessons from building AI agents in production:\\n\\n1. ...\",\n \"scheduled_time\": \"2024-01-28T09:00:00Z\",\n \"status\": \"pending\",\n \"media\": null\n }\n]\n\nEngagement Workflow\n\nRun scripts/engage.sh 3-4x daily. The script:\n\nSearches for posts matching target criteria (keywords, accounts, hashtags)\nScores relevance (content match, author influence, engagement level)\nEngages with top posts (like, thoughtful comment, or share)\nTracks engagement to avoid repeats\nRespects rate limits (20-30 engagements per run)\n\nTarget patterns:\n\nPosts from specific companies/people\nPosts with keywords/hashtags\nPosts in your feed from connections\nTrending posts in your industry\n\nEngagement types:\n\nLike: Quick signal, low friction\nComment: Generated from templates + post context (not spammy)\nShare: With your take/commentary added\nDM Sequence Workflow\n\nRun scripts/dm-sequence.sh daily. The script:\n\nChecks active sequences for people at each stage\nSends next message in sequence (respects delays)\nDetects replies and advances/pauses accordingly\nHandles conditional branching (replied vs not replied)\nReports on conversion rates\n\nSequence example:\n\n{\n \"name\": \"consulting-intro\",\n \"trigger\": \"new_connection\",\n \"steps\": [\n {\n \"delay_hours\": 24,\n \"message\": \"Hey {first_name}! Thanks for connecting. I help {title}s with {pain_point}. Are you currently working on anything in this space?\",\n \"condition\": null\n },\n {\n \"delay_hours\": 72,\n \"message\": \"Following up — I saw your post about {topic}. Would love to chat about {offering}. Free for a quick call this week?\",\n \"condition\": \"no_reply\"\n }\n ]\n}\n\nConnection Request Workflow\n\nRun scripts/connect.sh weekly (not daily — LinkedIn limits this). The script:\n\nSearches for target profiles (job titles, companies, keywords)\nFilters out existing connections and pending requests\nGenerates personalized connection notes\nSends requests with safety throttling (20-30/week max)\nTracks acceptance rate\n\nTarget criteria:\n\n\"connection_targets\": [\n {\n \"query\": \"AI consultant OR automation specialist\",\n \"companies\": [\"Microsoft\", \"Google\", \"OpenAI\"],\n \"exclude_titles\": [\"Recruiter\"],\n \"note_template\": \"Hey {first_name}, I'm building AI tools for {industry} and saw your work at {company}. Would love to connect!\"\n }\n]\n\nSafety & Rate Limits\n\nLinkedIn Autopilot follows conservative rate limits to avoid account flags:\n\nAction\tLimit\tTiming\nPosts\t1-2/day\tOptimal hours (9am-11am, 2pm-4pm)\nEngagements\t80-100/day\tSpread across 3-4 runs\nConnection Requests\t20-30/week\tGradual warmup over first 2 weeks\nDMs\t30-50/day\tRandom delays 5-15min between sends\nProfile Views\t50-80/day\tNatural browsing pattern\n\nWarmup Period: First 2 weeks run at 50% capacity to establish normal behavior pattern.\n\nBlackout Windows: No activity during nights/weekends (configurable).\n\nRandom Delays: 3-8 seconds between actions, 5-15 minutes between campaigns.\n\nHuman-Like Patterns: Varied engagement times, occasional skips, natural language variance.\n\nState Tracking\n\nAll activity is logged and tracked:\n\n~/.config/linkedin-autopilot/\n├── config.json # User configuration\n├── posts-queue.json # Scheduled posts\n├── engagement-history.json # Posts engaged with (dedup)\n├── dm-sequences.json # Active DM threads\n├── connections.json # Connection requests + status\n├── analytics.json # Performance metrics\n└── activity-log.json # Full audit trail\n\nReporting\n\nscripts/report.sh generates performance reports:\n\nWeekly Summary:\n\nPosts published (reach, engagement rate)\nEngagements performed (breakdown by type)\nConnection requests (sent, accepted, pending)\nDM sequences (active, replied, converted)\nGrowth metrics (followers, connections, profile views)\n\nLead Conversion Tracking:\n\nDM replies → qualified leads\nConnection acceptances → engaged conversations\nPost engagement → inbound interest\nExample Workflows\n1. Thought Leader Building\nPost 1x/day on schedule (industry insights, lessons learned)\nAuto-engage with 20-30 posts daily from influencers in your space\nShare top posts with your commentary\nTrack which content types drive the most profile views\n2. Outbound Lead Gen\nConnect with 20-30 target profiles weekly (ICP: CTOs at Series A startups)\nRun DM sequence on new connections (intro → value prop → call booking)\nAuto-engage with prospects' posts before sending sequence\nReport on reply rate and meeting bookings\n3. Network Maintenance\nLike posts from existing connections (stay top of mind)\nComment thoughtfully on key accounts' updates\nShare relevant content to your feed\nPeriodic check-ins via DM (birthday, work anniversary, post milestone)\nLinkedIn TOS Compliance\n\nImportant: LinkedIn's ToS prohibits automation. This tool is designed for:\n\nPersonal use with human oversight (you review/approve actions)\nAgent-assisted workflows (agent suggests, human approves)\nBatch scheduling (compose in bulk, post on schedule)\n\nRecommended approach:\n\nUse --dry-run mode to preview actions\nReview queued posts/messages before enabling auto-send\nSet conservative rate limits\nMonitor for account warnings\nAlways have a human in the loop for sensitive actions\n\nThis tool is provided as-is for educational purposes. Use responsibly.\n\nData Files\n~/.config/linkedin-autopilot/\n├── config.json # Main configuration\n├── posts-queue.json # Scheduled content\n├── engagement-history.json # Activity dedup\n├── dm-sequences.json # Active conversations\n├── connections.json # Network building state\n├── analytics.json # Performance tracking\n└── activity-log.json # Full audit trail\n\nBrowser Automation\n\nUses Clawdbot's built-in browser control:\n\nSnapshot → Act → Verify pattern\nHandles login, 2FA prompts, session management\nRetries on rate limit detection\nGraceful handling of LinkedIn UI changes\nAdvanced Features\n\nA/B Testing: Test post variants, measure which performs better\n\nSmart Scheduling: ML-based optimal posting time suggestion\n\nReply Detection: Pauses DM sequences when prospect replies\n\nSentiment Analysis: Adjusts engagement strategy based on post sentiment\n\nNetwork Mapping: Tracks who engages with your content (potential advocates)\n\nTroubleshooting\n\n\"LinkedIn security check triggered\"\n→ Reduce rate limits in config, extend delays, complete security verification manually\n\n\"Posts not publishing\"\n→ Check activity-log.json for errors, verify LinkedIn session still valid\n\n\"DM sequences not advancing\"\n→ Verify reply detection is working, check conversation state in dm-sequences.json\n\n\"Connection requests rejected frequently\"\n→ Improve note personalization, target better ICP matches, reduce volume\n\nContributing\n\nWant to add features? See references/linkedin-api.md for browser automation patterns and references/sequence-engine.md for DM workflow logic.\n\nRemember: Your agent is a force multiplier, not a replacement for authentic networking. Use it to handle the tedious parts so you can focus on the conversations that matter." }, "trust": { "sourceLabel": "tencent", "provenanceUrl": "https://clawhub.ai/audsmith28/linkedin-autopilot", "publisherUrl": "https://clawhub.ai/audsmith28/linkedin-autopilot", "owner": "audsmith28", "version": "1.1.0", "license": null, "verificationStatus": "Indexed source record" }, "links": { "detailUrl": "https://openagent3.xyz/skills/linkedin-autopilot", "downloadUrl": "https://openagent3.xyz/downloads/linkedin-autopilot", "agentUrl": "https://openagent3.xyz/skills/linkedin-autopilot/agent", "manifestUrl": "https://openagent3.xyz/skills/linkedin-autopilot/agent.json", "briefUrl": "https://openagent3.xyz/skills/linkedin-autopilot/agent.md" } }