claude

linkedin-commander

9 AI agents as a marketing team: content strategy, post analysis, lead generation, competitor tracking. Delta-based pipeline with human-in-the-loop.

10 on GitHubby Arben Sabaniv3.0.3MITupdated 7 months ago
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Plugin linkedin-commander from marketplace sabania-linkedin-cli in sabania/linkedin-cli. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (12)

  • analyze

    Analyze post performance. Compares with baseline, detects patterns, evaluates experiments, analyzes comments, updates ICP. Lifecycle-aware.

  • auto

    Morning Check / Session Entry Point. Delta pipeline: Stage 1 COLLECT → Stage 2 DETECT (+ Feed parallel). On-the-fly engagement analysis, no stored contacts.

  • check

    Quick status check without API calls. Shows current state from data files + session info.

  • competitor

    Analyze competitors. Evaluate posts, engagement, content strategy and extract learnings.

  • data-schema

    Complete data schema for LinkedIn tracking. Markdown file-per-record with YAML frontmatter. Naming conventions, schemas for all 11 record types, Glob/Read/Write/Edit access patterns.

  • draft

    Create a new LinkedIn post or strategic comment. Uses brand voice, strategy, and patterns. +Comment draft mode.

  • evolve

    Evolve content strategy. Orchestrates strategy-evolver agent. Human gate for new versions. Weekly during Weekly Review or on-demand.

  • ideas

    Generate content ideas from 8 sources. Feed Trends, Competitor Gaps, Repurposing, Patterns, News, Experiments, Audience Requests, User Input.

  • linkedin-cli-reference

    Complete reference for the linkedin-cli tool. Load this skill when you need to call the CLI via Bash to fetch LinkedIn data, manage connections, or send messages.

  • outreach

    Generate personalized outreach message for a LinkedIn contact.

  • report

    Create weekly performance report with KPIs, trends, and insights.

  • setup

    Deep onboarding for LinkedIn Commander. Interview + historical post analysis + competitor deep dives + system generation. The system starts "warmed up", not empty.

Subagents (8)

  • competitor-analyst

    Market Researcher on the marketing team. Analyzes LinkedIn competitors. Initial deep dive and delta updates. On-demand for /competitor, periodically during Weekly Review (if >2 weeks old).

  • content-writer

    Content Creator on the marketing team. Writes LinkedIn posts, generates ideas from 8 sources, drafts outreach messages and comment drafts. On-demand for /ideas, /draft, /outreach.

  • data-collector

    Data Analyst on the marketing team. Collects delta data via Notifications (1 API call = 80% of deltas) and active post analytics. Auto-discovers new posts. Manages post archive. Pipeline Stage 1: COLLECT.

  • feed-analyst

    Social Media Scout on the marketing team. Monitors the feed for trends, comment opportunities, competitor posts. Pipeline Stage 3b: DETECT (parallel to signal-detector).

  • post-analyzer

    Performance Analyst on the marketing team. Analyzes posts, detects patterns (incl. combinations), evaluates experiments, updates ICP Profile. Weekly for /report + on-demand for /analyze.

  • report-builder

    Reporting Analyst on the marketing team. Creates weekly performance reports. Aggregates metrics, shows trends, compares with competitors, tracks ICP alignment.

  • signal-detector

    Intelligence Officer on the marketing team. Detects signals through on-the-fly engagement analysis and cross-referencing. Pipeline Stage 2: DETECT. Receives engagement data from data-collector (Stage 1).

  • strategy-evolver

    Head of Strategy on the marketing team. THE Learning Loop. Evolves the content strategy based on patterns, ICP data, competitor insights, and performance trends. Human gate for new versions.

View source on GitHub

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Complete command reference for linkedin-cli. Gives AI agents the knowledge to use all CLI commands with correct syntax, flags, and JSON output shapes.

1 skill

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