Skill: jclvsh/dropspace-content-engine (version 1.0.1)

--- name: dropspace-content-engine description: "Self-improving autonomous content pipeline. Analyzes post performance across 6 platforms, generates new content with AI (slideshows, tweets, linkedin posts, reddit threads), schedules via Dropspace API. Gets smarter every night — each cycle learns from real engagement data. Use when asked to set up autonomous content posting, run the content engine, or manage multi-platform social media automation." homepage: https://www.dropspace.dev/community/dropspace-content-engine source: https://github.com/joshchoi4881/dropspace-agents metadata: { "openclaw": { "emoji": "🔄", "requires": { "env": ["DROPSPACE_API_KEY", "ANTHROPIC_API_KEY", "FAL_KEY"], "install": "git clone https://github.com/joshchoi4881/dropspace-agents && cd dropspace-agents && npm install" } } } --- # Dropspace Content Engine Fully autonomous content pipeline. Every night: pull analytics → identify winning hooks → generate new posts → schedule across 6 platforms. The feedback loop compounds — each cycle produces better content because it learns from real engagement data. ## Setup ### 1. Clone and install ```bash git clone https://github.com/joshchoi4881/dropspace-agents && cd dropspace-agents && npm install ``` If `canvas` fails to install, that's fine — text-only formats still work. For visual formats (TikTok/Instagram slideshows): macOS `brew install pkg-config cairo pango`, Linux `apt install libcairo2-dev libpango1.0-dev`, then `npm install` again. ### 2. Run the setup wizard ```bash node setup.js --template dropspace-content-engine ``` Walks you through API keys, platform selection, and app configuration. ### 3. Set your API keys ```bash export DROPSPACE_API_KEY="ds_live_..." # from dropspace.dev/settings/api export ANTHROPIC_API_KEY="sk-ant-..." # from console.anthropic.com export FAL_KEY="fal_..." # from fal.ai (for visual/video formats) ``` Save in a `.env` file (copy from `templates/.env.example`). Add `.env` to `.gitignore` to avoid committing secrets. ### 4. Validate ```bash node scripts/test-pipeline.js --app myapp ``` ## Run the Pipeline ```bash source .env # Analyze performance + generate new posts node scripts/run-self-improve-all.js --app myapp # Schedule generated posts for today node scripts/schedule-day.js --app myapp ``` ## Automate Nightly | Time (ET) | Script | What | |-----------|--------|------| | 12:00 AM | `scripts/refresh-tracking.js --all` + `scripts/cleanup-posts.js --all` | Refresh analytics, clean old media | | 12:30 AM | `scripts/run-x-research.js --app myapp` | Scan X for trending hooks (optional, needs Bird CLI) | | 1:00 AM | `scripts/run-self-improve-all.js --app myapp` | Analyze + generate (up to 60 min) | | 2:00 AM | `scripts/schedule-day.js --app myapp` | Schedule for today | ## What Happens Each Run 1. Pulls 14 days of analytics from Dropspace API 2. Identifies winning hooks (posts with >2x average engagement) 3. Cross-references with X/Twitter research signals 4. Generates 7-14 new posts with AI (text, visual, video formats) 5. Fact-checks any claims about people, products, or events 6. Writes strategy notes that persist between runs (the loop compounds) 7. Schedules posts across the day via Dropspace API ## Content Formats | Format | Type | Platforms | |--------|------|-----------| | story-slideshow | visual | TikTok, Instagram, Facebook | | ugc-reaction | video | TikTok, Instagram | | text-single | text | Twitter/X | | text-post | text | LinkedIn, Reddit, Facebook | ## Links - Community page: https://www.dropspace.dev/community/dropspace-content-engine - Case study: https://www.dropspace.dev/case-studies/march-2026 - Repo: https://github.com/joshchoi4881/dropspace-agents - Dropspace API docs: https://www.dropspace.dev/docs


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)