{"slug":"sergebulaev-linkedin-engager-analytics","name":"linkedin-engager-analytics","description":"Pull the people who liked or commented on any LinkedIn post and segment them by ICP fit (peer / aspirational / prospect / other). Produces an engager roster, tier breakdown, and outbound action lists (follow back, comment-drop, DM-able with one-line openers). Powered by Apify, no LinkedIn login. Triggers on \"who liked my post\", \"who engaged\", \"engagers report\", \"audience analytics\". Not for tracking author replies to your comments (use linkedin-thread-monitor).","long_description":"---\nname: linkedin-engager-analytics\ndescription: Pull the people who liked or commented on any LinkedIn post and segment them by ICP fit (peer / aspirational / prospect / other). Produces an engager roster, tier breakdown, and outbound action lists (follow back, comment-drop, DM-able with one-line openers). Powered by Apify, no LinkedIn login. Triggers on \"who liked my post\", \"who engaged\", \"engagers report\", \"audience analytics\". Not for tracking author replies to your comments (use linkedin-thread-monitor).\n---\n\n# LinkedIn Engager Analytics\n\nPull every liker and commenter on a LinkedIn post and bucket them by ICP fit. Outputs a roster + action list you can feed into your DM or outreach queue.\n\nDepends on `APIFY_TOKEN`. Without it, falls back to user-paste of the engager list.\n\n## When to use\n\n- After publishing a post: \"Who actually engaged? Are they ICP?\"\n- Before a campaign: \"Pull the last 5 viral posts in my niche, group their commenters by company size\"\n- Reviewing competitor engagement: which prospects show up across multiple authors\n\n## Input\n\n- One or more LinkedIn post URLs\n- Optional: ICP definition (target titles, company size, industry)\n- Optional: max engagers per post (default 100)\n\n## Output\n\nOutput format (engager roster, tier breakdown, action lists): see `references/output-spec.md`. Headline: a table of engagers labelled by ICP tier and a per-tier action list.\n\n## Steps\n\n1. **Fetch engagers.** Call `lib.ApifyClient.fetch_post_engagers(post_url=<url>, max_items=100)`. Returns a list of dicts with `type` (\"commenters\" | \"likers\"), `name`, `subtitle` (job title + company), `url_profile`, `content` (comment text if commenter), `datetime`. Cost is roughly $0.005 per engager-record.\n2. **Parse subtitle into structured fields.** The `subtitle` typically reads \"Director at Acme Corp\" or \"Founder & CEO at SaaS Inc\". Extract: title, company, seniority bucket (IC / Manager / Director / VP / C-suite / Founder).\n3. **Score ICP fit.** Use the user's supplied ICP rules:\n   - Title match (regex or keyword list)\n   - Company size proxy (look up via the user's CRM if integrated, else mark Unknown)\n   - Industry match (parse company name + subtitle keywords)\n4. **Assign tier.**\n   - Peer: founder / operator at similar-stage company in same niche\n   - Aspirational: senior leader (Director+) at larger company in adjacent niche\n   - Prospect: title in ICP target list AND company in ICP target list\n   - Other: no match\n5. **Produce action lists.**\n   - Follow back: peers with active posting (heuristic: appears as author in `fetch_user_recent_comments` of any team member)\n   - Comment-drop targets: aspirational tier\n   - DM-able: prospect tier, with a one-line DM opener referencing the specific post they engaged with (\"Saw you reacted to <post angle>. Curious. Are you currently <ICP problem>?\")\n6. **Optional cross-post analysis.** If the user supplied multiple post URLs, deduplicate engagers and flag people who engaged with 2+ posts (highest-intent signal).\n\n## Inbound-quality signals\n\nHigh-quality = follow up: founder/operator title, company in ICP, active posting history, >10 mutual 2nd-degree connections, prior thoughtful comments on user's posts.\n\nLow-quality = skip: generic praise, template language (\"I'd love to hop on a quick call\"), sales/agency profile with no operator history, same comment copy-pasted across many creators.\n\n## Hard rules\n\nGlobal voice rules: see root `SKILL.md` §Voice rules. Additional skill-specific rules:\n\n- Don't run engager analytics on posts you didn't write or aren't tracking with permission. The data is technically public but high-volume scraping of someone else's audience reads as creepy.\n- Don't DM a prospect on the same day they engaged with your post. Wait 24-72h to avoid the \"thirsty\" pattern.\n- One DM opener per engager, not three. If the first didn't land in 5 business days, drop it.\n\n## Cost accounting\n\n| Action | Apify call | Cost (free tier) |\n|---|---|---|\n| Engager analytics on one post (50 engagers) | `fetch_post_engagers(max_items=50)` | $0.25 |\n| Engager analytics on one post (200 engagers) | `fetch_post_engagers(max_items=200)` | $1.00 |\n\nA weekly engager-analytics run on 1-2 posts stays well under the $5 free monthly credit.\n\n## Files\n\n- `SKILL.md` — this file\n- `references/output-spec.md` — engager roster shape, tier breakdown, action lists, sample run\n\n## Related skills\n\n- `linkedin-thread-monitor` — track author replies to YOUR comments (different surface)\n- `linkedin-comment-drafter` — draft outreach comments to engagers from this report\n- `linkedin-reply-handler` — draft DM follow-ups\n","tagline":"Pull the people who liked or commented on any LinkedIn post and segment them by ICP fit (peer / aspirational / prospect / other). Produces an engager roster, tier breakdown, and outbound action lists (follow back, comment-drop, DM-able with one-line openers). Powered by Apify, no","category":"research","tags":["agent-skill"],"author":"sergebulaev","verified":false,"attribution":{"status":"registry_indexed","statusLabel":"Registry indexed","shortLabel":"REGISTRY INDEXED","sourceLabel":"github fast track","sourceDetail":"sergebulaev/linkedin-skills","creatorName":"sergebulaev","creatorUrl":"https://github.com/sergebulaev","sourceUrl":"https://github.com/sergebulaev/linkedin-skills/tree/main/skills/linkedin-engager-analytics","indexedBy":"OpenAgentSkill community index","claimUrl":"https://www.openagentskill.com/skills/sergebulaev-linkedin-engager-analytics#claim-this-skill","claimCta":"Claim this skill","trustNote":"This listing was indexed from public sources and is not marked official until a maintainer claim is approved.","publicNote":"Attribution links to the public repository or creator profile. 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Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"outcome_stats":null,"safety":{"score":68,"level":"review_before_install","label":"Review before install","safety_tier":{"tier":"reviewed","label":"Reviewed","badge":"REVIEWED","summary":"Good audit and safety signals with no high-risk permission hints in public metadata.","recommended_action":"Review the audit page, then allow agent install in a sandboxed workflow.","auto_install_policy":"review","reasons":["Safe-to-try audit","68/100 agent safety score"]},"auto_install_allowed":false,"human_review_required":true,"blocked":false,"audit_risk":"safe_to_try","permission_hints":[{"id":"network","label":"Network access","reason":"Skill likely fetches remote pages, APIs, repositories, or external services.","severity":"medium"},{"id":"filesystem","label":"Filesystem access","reason":"Skill may read or write project files, documents, generated artifacts, or local workspace state.","severity":"medium"}],"policy_warnings":["Quality score needs review"],"constraints_applied":{"max_risk":"medium","needs_install_command":true,"min_stars":0}},"safety_gate":{"tier":"reviewed","label":"Reviewed","badge":"REVIEWED","auto_install_policy":"review","auto_install_allowed":false,"blocked":false,"human_review_required":true,"recommended_action":"Review the audit page, then allow agent install in a sandboxed workflow.","reasons":["Safe-to-try audit","68/100 agent safety score"]},"eval":{"version":"openagentskill-skill-eval-v1","status":"review","score":78,"risk_level":"medium","decision":{"recommendation":"manual_review","reason":"Review the audit page, then allow agent install in a sandboxed workflow.","auto_install_allowed":false,"policy":"review","human_review_required":true},"blockers":[],"warnings":["Agent safety gate: Good audit and safety signals with no high-risk permission hints in public metadata.","Permission surface: filesystem or document access, network or browser access","Quality score needs review"],"validation_plan":["Inspect repository, README/SKILL.md, license, and recent commits before production use.","Install in an isolated workspace or sandbox with no production secrets available.","Run the smallest representative task and record files touched, commands run, network access, and outputs.","Compare the selected skill against at least one alternative when the eval status is review or failed.","Promote only after the agent reports a successful verification result and unresolved warnings are accepted."],"checks":[{"id":"task_fit","label":"Task fit","status":"pass","score":84,"required_for_auto_install":true,"detail":"Task wording matches this skill metadata.","evidence":["Evaluate linkedin-engager-analytics before installing it in an agent workflow","research","Sales and CRM workflows; Claude Code teams; teams that value GitHub adoption signals"]},{"id":"install_path","label":"Install path","status":"pass","score":92,"required_for_auto_install":true,"detail":"Install handoff is available.","evidence":["npx skills add sergebulaev/linkedin-skills --skill linkedin-engager-analytics"]},{"id":"install_safety","label":"Install command safety","status":"pass","score":92,"required_for_auto_install":true,"detail":"standard package or runtime install path","evidence":["npx skills add sergebulaev/linkedin-skills --skill linkedin-engager-analytics"]},{"id":"trust_score","label":"Trust score","status":"pass","score":82,"required_for_auto_install":true,"detail":"Good trust signals with a few areas worth checking before rollout.","evidence":["Strong shortlist","652 GitHub stars","MIT"]},{"id":"audit_score","label":"Audit score","status":"pass","score":84,"required_for_auto_install":true,"detail":"Safe to try","evidence":["Quality score needs review"]},{"id":"agent_safety_gate","label":"Agent safety gate","status":"warn","score":68,"required_for_auto_install":true,"detail":"Good audit and safety signals with no high-risk permission hints in public metadata.","evidence":["Review the audit page, then allow agent install in a sandboxed workflow.","Safe-to-try audit"]},{"id":"readme_skillmd_completeness","label":"README/SKILL.md completeness","status":"pass","score":86,"required_for_auto_install":false,"detail":"Metadata includes enough usage and workflow context","evidence":["Strong README/SKILL.md context"]},{"id":"license_clarity","label":"License clarity","status":"pass","score":86,"required_for_auto_install":true,"detail":"MIT","evidence":["MIT"]},{"id":"recent_maintenance","label":"Recent maintenance","status":"pass","score":100,"required_for_auto_install":false,"detail":"5d since push","evidence":["5d since push"]},{"id":"permission_surface","label":"Permission surface","status":"warn","score":72,"required_for_auto_install":true,"detail":"filesystem or document access, network or browser access","evidence":["Network access: medium","Filesystem access: medium"]},{"id":"alternatives","label":"Alternatives available","status":"info","score":55,"required_for_auto_install":false,"detail":"No close alternatives were found in the current shortlist.","evidence":[]}],"endpoints":{"web":"https://www.openagentskill.com/skills/sergebulaev-linkedin-engager-analytics/evals","api":"/api/agent/evals?slug=sergebulaev-linkedin-engager-analytics","text":"/api/agent/evals?slug=sergebulaev-linkedin-engager-analytics&format=text"}},"agent_readable_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"sergebulaev-linkedin-engager-analytics","name":"linkedin-engager-analytics","description":"Pull the people who liked or commented on any LinkedIn post and segment them by ICP fit (peer / aspirational / prospect / other). Produces an engager roster, tier breakdown, and outbound action lists (follow back, comment-drop, DM-able with one-line openers). Powered by Apify, no LinkedIn login. Triggers on \"who liked my post\", \"who engaged\", \"engagers report\", \"audience analytics\". Not for tracking author replies to your comments (use linkedin-thread-monitor).","category":"research","url":"https://www.openagentskill.com/skills/sergebulaev-linkedin-engager-analytics","repository":"https://github.com/sergebulaev/linkedin-skills/tree/main/skills/linkedin-engager-analytics","github_repo":"sergebulaev/linkedin-skills"},"suited_tasks":["Sales and CRM workflows","Claude Code teams","teams that value GitHub adoption signals","Research accounts","Extract contact details","Write structured CRM updates","Search sources","Extract claims"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add sergebulaev/linkedin-skills --skill linkedin-engager-analytics","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add sergebulaev-linkedin-engager-analytics"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"linkedin-engager-analytics\" agent skill from https://github.com/sergebulaev/linkedin-skills/tree/main/skills/linkedin-engager-analytics. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Pull the people who liked or commented on any LinkedIn post and segment them by ICP fit (peer / aspirational / prospect / other). Produces an engager roster, tier breakdown, and outbound action lists (follow back, comment-drop, DM-able with one-line openers). Powered by Apify, no LinkedIn login. Triggers on \"who liked my post\", \"who engaged\", \"engagers report\", \"audience analytics\". Not for tracking author replies to your comments (use linkedin-thread-monitor). After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"sergebulaev-linkedin-engager-analytics\",\"task\":\"Install linkedin-engager-analytics\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"linkedin-engager-analytics\" as a Claude Code skill from https://github.com/sergebulaev/linkedin-skills/tree/main/skills/linkedin-engager-analytics. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Pull the people who liked or commented on any LinkedIn post and segment them by ICP fit (peer / aspirational / prospect / other). Produces an engager roster, tier breakdown, and outbound action lists (follow back, comment-drop, DM-able with one-line openers). Powered by Apify, no LinkedIn login. Triggers on \"who liked my post\", \"who engaged\", \"engagers report\", \"audience analytics\". Not for tracking author replies to your comments (use linkedin-thread-monitor). After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"sergebulaev-linkedin-engager-analytics\",\"task\":\"Install linkedin-engager-analytics\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"linkedin-engager-analytics\" from https://github.com/sergebulaev/linkedin-skills/tree/main/skills/linkedin-engager-analytics into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Pull the people who liked or commented on any LinkedIn post and segment them by ICP fit (peer / aspirational / prospect / other). Produces an engager roster, tier breakdown, and outbound action lists (follow back, comment-drop, DM-able with one-line openers). Powered by Apify, no LinkedIn login. Triggers on \"who liked my post\", \"who engaged\", \"engagers report\", \"audience analytics\". Not for tracking author replies to your comments (use linkedin-thread-monitor). After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"sergebulaev-linkedin-engager-analytics\",\"task\":\"Install linkedin-engager-analytics\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/sergebulaev-linkedin-engager-analytics/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/sergebulaev-linkedin-engager-analytics"},"trust":{"score":82,"label":"Strong shortlist","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"652 GitHub stars","repoActivity":"652 stars, 99 forks","lastPushed":"5d since push","license":"MIT","repository":"https://github.com/sergebulaev/linkedin-skills/tree/main/skills/linkedin-engager-analytics","install":"npx skills add sergebulaev/linkedin-skills --skill linkedin-engager-analytics","installSafety":"standard package or runtime install path","permissionSurface":"filesystem or document access, network or browser access","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["research","agent-skill"],"known_risks":["Quality score needs review"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":84,"risk_level":"safe_to_try","risk_label":"Safe to try","warnings":["Quality score needs review"]},"safety_gate":{"tier":"reviewed","label":"Reviewed","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Review the audit page, then allow agent install in a sandboxed workflow."},"quality":{"score":75,"label":"Strong"},"supply":{"track":"Research and knowledge work","scenario":"Research agents","maintenance":"5d since push","risk":"Safe to try"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","high-compliance environments without internal security review","No OpenAgentSkill engagement data yet","Quality score needs review","Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace"],"agent_contract":{"task_input":"Use linkedin-engager-analytics in an agent workflow","recommended_action":"Review the audit page, then allow agent install in a sandboxed workflow.","install_policy":"review","minimum_review_before_use":["Trust: 82/100 Strong shortlist","Audit: 84/100 Safe to try","Safety: 68/100 Review before install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"sergebulaev-linkedin-engager-analytics (linkedin-engager-analytics)","install_command":"npx skills add sergebulaev/linkedin-skills --skill linkedin-engager-analytics","risk_summary":"Safe to try; Reviewed; Low metadata risk","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"sergebulaev-linkedin-engager-analytics","task":"Use linkedin-engager-analytics in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/sergebulaev-linkedin-engager-analytics","api":"https://www.openagentskill.com/api/agent/skills/sergebulaev-linkedin-engager-analytics","audit":"https://www.openagentskill.com/skills/sergebulaev-linkedin-engager-analytics/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=sergebulaev-linkedin-engager-analytics&task=Use%20linkedin-engager-analytics%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20linkedin-engager-analytics%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20linkedin-engager-analytics%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/sergebulaev-linkedin-engager-analytics/install","manifest":"https://www.openagentskill.com/api/registry/manifest/sergebulaev-linkedin-engager-analytics"}},"machine_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"sergebulaev-linkedin-engager-analytics","name":"linkedin-engager-analytics","description":"Pull the people who liked or commented on any LinkedIn post and segment them by ICP fit (peer / aspirational / prospect / other). Produces an engager roster, tier breakdown, and outbound action lists (follow back, comment-drop, DM-able with one-line openers). Powered by Apify, no LinkedIn login. Triggers on \"who liked my post\", \"who engaged\", \"engagers report\", \"audience analytics\". Not for tracking author replies to your comments (use linkedin-thread-monitor).","category":"research","url":"https://www.openagentskill.com/skills/sergebulaev-linkedin-engager-analytics","repository":"https://github.com/sergebulaev/linkedin-skills/tree/main/skills/linkedin-engager-analytics","github_repo":"sergebulaev/linkedin-skills"},"suited_tasks":["Sales and CRM workflows","Claude Code teams","teams that value GitHub adoption signals","Research accounts","Extract contact details","Write structured CRM updates","Search sources","Extract claims"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add sergebulaev/linkedin-skills --skill linkedin-engager-analytics","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add sergebulaev-linkedin-engager-analytics"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"linkedin-engager-analytics\" agent skill from https://github.com/sergebulaev/linkedin-skills/tree/main/skills/linkedin-engager-analytics. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Pull the people who liked or commented on any LinkedIn post and segment them by ICP fit (peer / aspirational / prospect / other). Produces an engager roster, tier breakdown, and outbound action lists (follow back, comment-drop, DM-able with one-line openers). Powered by Apify, no LinkedIn login. Triggers on \"who liked my post\", \"who engaged\", \"engagers report\", \"audience analytics\". Not for tracking author replies to your comments (use linkedin-thread-monitor). After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"sergebulaev-linkedin-engager-analytics\",\"task\":\"Install linkedin-engager-analytics\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"linkedin-engager-analytics\" as a Claude Code skill from https://github.com/sergebulaev/linkedin-skills/tree/main/skills/linkedin-engager-analytics. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Pull the people who liked or commented on any LinkedIn post and segment them by ICP fit (peer / aspirational / prospect / other). Produces an engager roster, tier breakdown, and outbound action lists (follow back, comment-drop, DM-able with one-line openers). Powered by Apify, no LinkedIn login. Triggers on \"who liked my post\", \"who engaged\", \"engagers report\", \"audience analytics\". Not for tracking author replies to your comments (use linkedin-thread-monitor). After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"sergebulaev-linkedin-engager-analytics\",\"task\":\"Install linkedin-engager-analytics\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"linkedin-engager-analytics\" from https://github.com/sergebulaev/linkedin-skills/tree/main/skills/linkedin-engager-analytics into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Pull the people who liked or commented on any LinkedIn post and segment them by ICP fit (peer / aspirational / prospect / other). Produces an engager roster, tier breakdown, and outbound action lists (follow back, comment-drop, DM-able with one-line openers). Powered by Apify, no LinkedIn login. Triggers on \"who liked my post\", \"who engaged\", \"engagers report\", \"audience analytics\". Not for tracking author replies to your comments (use linkedin-thread-monitor). After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"sergebulaev-linkedin-engager-analytics\",\"task\":\"Install linkedin-engager-analytics\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/sergebulaev-linkedin-engager-analytics/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/sergebulaev-linkedin-engager-analytics"},"trust":{"score":82,"label":"Strong shortlist","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"652 GitHub stars","repoActivity":"652 stars, 99 forks","lastPushed":"5d since push","license":"MIT","repository":"https://github.com/sergebulaev/linkedin-skills/tree/main/skills/linkedin-engager-analytics","install":"npx skills add sergebulaev/linkedin-skills --skill linkedin-engager-analytics","installSafety":"standard package or runtime install path","permissionSurface":"filesystem or document access, network or browser access","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["research","agent-skill"],"known_risks":["Quality score needs review"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":84,"risk_level":"safe_to_try","risk_label":"Safe to try","warnings":["Quality score needs review"]},"safety_gate":{"tier":"reviewed","label":"Reviewed","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Review the audit page, then allow agent install in a sandboxed workflow."},"quality":{"score":75,"label":"Strong"},"supply":{"track":"Research and knowledge work","scenario":"Research agents","maintenance":"5d since push","risk":"Safe to try"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","high-compliance environments without internal security review","No OpenAgentSkill engagement data yet","Quality score needs review","Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace"],"agent_contract":{"task_input":"Use linkedin-engager-analytics in an agent workflow","recommended_action":"Review the audit page, then allow agent install in a sandboxed workflow.","install_policy":"review","minimum_review_before_use":["Trust: 82/100 Strong shortlist","Audit: 84/100 Safe to try","Safety: 68/100 Review before install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"sergebulaev-linkedin-engager-analytics (linkedin-engager-analytics)","install_command":"npx skills add sergebulaev/linkedin-skills --skill linkedin-engager-analytics","risk_summary":"Safe to try; Reviewed; Low metadata risk","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"sergebulaev-linkedin-engager-analytics","task":"Use linkedin-engager-analytics in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/sergebulaev-linkedin-engager-analytics","api":"https://www.openagentskill.com/api/agent/skills/sergebulaev-linkedin-engager-analytics","audit":"https://www.openagentskill.com/skills/sergebulaev-linkedin-engager-analytics/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=sergebulaev-linkedin-engager-analytics&task=Use%20linkedin-engager-analytics%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20linkedin-engager-analytics%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20linkedin-engager-analytics%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/sergebulaev-linkedin-engager-analytics/install","manifest":"https://www.openagentskill.com/api/registry/manifest/sergebulaev-linkedin-engager-analytics"}},"supply_profile":{"track":{"slug":"research","label":"Research and knowledge work","shortLabel":"Research","description":"Deep research, source comparison, literature review, RAG, knowledge search, and reports."},"scenario":{"label":"Research agents","description":"I need my agent to research a topic, compare sources, and produce a concise report.","useCases":[{"slug":"sales-crm","title":"Sales and CRM"},{"slug":"research-agents","title":"Research agents"},{"slug":"document-processing","title":"Document processing"}]},"applicableAgents":["Claude Code","CLI","Codex","Cursor"],"install":{"ready":true,"command":"npx skills add sergebulaev/linkedin-skills --skill linkedin-engager-analytics","primaryTarget":"CLI","targetCount":4},"githubQuality":{"stars":652,"starsLabel":"652","forks":99,"license":"MIT","qualityScore":75,"trustScore":82,"auditScore":84},"maintenance":{"status":"fresh","label":"5d since push","daysSincePush":5,"lastPushedAt":"2026-09-01T11:11:10+00:00"},"risk":{"level":"safe_to_try","label":"Safe to try","requiresReview":true,"notes":["Quality score needs review"]},"coverageTags":["Research","Research agents","agent-skill"]},"audit":{"audit_score":84,"risk_level":"safe_to_try","risk_label":"Safe to try","quality_score":75,"trust_score":82,"maintenance_score":100,"security_score":86,"install_score":92,"warnings":["Quality score needs review"]},"quality_signals":{"model":"v2","star_score":19.7,"usage_score":0,"review_score":5.1,"metadata_score":3,"freshness_score":15},"platforms":["Claude Code"],"use_cases":[{"slug":"sales-crm","title":"Sales and CRM","url":"https://www.openagentskill.com/use-cases/sales-crm"},{"slug":"research-agents","title":"Research agents","url":"https://www.openagentskill.com/use-cases/research-agents"},{"slug":"document-processing","title":"Document processing","url":"https://www.openagentskill.com/use-cases/document-processing"},{"slug":"sports-analytics","title":"Sports analytics","url":"https://www.openagentskill.com/use-cases/sports-analytics"}],"stacks":[{"slug":"research-report-agent","title":"Research report agent","url":"https://www.openagentskill.com/collections/research-report-agent"},{"slug":"browser-qa-agent","title":"Browser QA agent","url":"https://www.openagentskill.com/collections/browser-qa-agent"},{"slug":"web-data-pipeline","title":"Web data pipeline","url":"https://www.openagentskill.com/collections/web-data-pipeline"}],"install":"npx skills add sergebulaev/linkedin-skills --skill linkedin-engager-analytics","install_targets":[{"id":"openagentskill-cli","label":"CLI","title":"OpenAgentSkill CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add sergebulaev-linkedin-engager-analytics","description":"Resolve policy, run the source installer safely, and report a verified install receipt.","copyLabel":"Copy command"},{"id":"codex","label":"Codex","title":"Codex install prompt","kind":"agent-prompt","value":"Install the \"linkedin-engager-analytics\" agent skill from https://github.com/sergebulaev/linkedin-skills/tree/main/skills/linkedin-engager-analytics. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Pull the people who liked or commented on any LinkedIn post and segment them by ICP fit (peer / aspirational / prospect / other). Produces an engager roster, tier breakdown, and outbound action lists (follow back, comment-drop, DM-able with one-line openers). Powered by Apify, no LinkedIn login. Triggers on \"who liked my post\", \"who engaged\", \"engagers report\", \"audience analytics\". Not for tracking author replies to your comments (use linkedin-thread-monitor). After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"sergebulaev-linkedin-engager-analytics\",\"task\":\"Install linkedin-engager-analytics\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Give Codex a repo-aware install prompt when the skill is not available through a local CLI.","copyLabel":"Copy prompt"},{"id":"claude-code","label":"Claude Code","title":"Claude Code skill prompt","kind":"agent-prompt","value":"Add \"linkedin-engager-analytics\" as a Claude Code skill from https://github.com/sergebulaev/linkedin-skills/tree/main/skills/linkedin-engager-analytics. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Pull the people who liked or commented on any LinkedIn post and segment them by ICP fit (peer / aspirational / prospect / other). Produces an engager roster, tier breakdown, and outbound action lists (follow back, comment-drop, DM-able with one-line openers). Powered by Apify, no LinkedIn login. Triggers on \"who liked my post\", \"who engaged\", \"engagers report\", \"audience analytics\". Not for tracking author replies to your comments (use linkedin-thread-monitor). After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"sergebulaev-linkedin-engager-analytics\",\"task\":\"Install linkedin-engager-analytics\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this prompt to ask Claude Code to add the skill and explain the local activation steps.","copyLabel":"Copy prompt"},{"id":"cursor","label":"Cursor","title":"Cursor rule prompt","kind":"agent-prompt","value":"Turn \"linkedin-engager-analytics\" from https://github.com/sergebulaev/linkedin-skills/tree/main/skills/linkedin-engager-analytics into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Pull the people who liked or commented on any LinkedIn post and segment them by ICP fit (peer / aspirational / prospect / other). Produces an engager roster, tier breakdown, and outbound action lists (follow back, comment-drop, DM-able with one-line openers). Powered by Apify, no LinkedIn login. Triggers on \"who liked my post\", \"who engaged\", \"engagers report\", \"audience analytics\". Not for tracking author replies to your comments (use linkedin-thread-monitor). After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"sergebulaev-linkedin-engager-analytics\",\"task\":\"Install linkedin-engager-analytics\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this when installing as Cursor project rules or reusable agent instructions.","copyLabel":"Copy prompt"}],"repository":"https://github.com/sergebulaev/linkedin-skills/tree/main/skills/linkedin-engager-analytics","github_repo":"sergebulaev/linkedin-skills","version":"1.0.0","license":"MIT","urls":{"web":"https://www.openagentskill.com/skills/sergebulaev-linkedin-engager-analytics","repository":"https://github.com/sergebulaev/linkedin-skills/tree/main/skills/linkedin-engager-analytics","api":"/api/agent/skills/sergebulaev-linkedin-engager-analytics","install_api":"/api/skills/sergebulaev-linkedin-engager-analytics/install"},"meta":{"created_at":"2026-09-03T01:55:37.10198+00:00","updated_at":"2026-09-03T01:55:37.153325+00:00","agent_friendly":true}}