🦉 OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation
- agent
- artificial-intelligence
- multi-agent-systems
- task-automation
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🦉 OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation
🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org
Stealth headless browser for AI agents — bypass Cloudflare, bot detection, and anti-scraping. Drop-in Puppeteer/Playwright replacement.
Motion films that never cut to the next slide: every beat grows out of the one before, one continuous camera, continuity measured by an oracle. Product launch films and feature demos, made with a coding agent.
Agent skill that turns Claude Code / Codex into a motion-design studio for voiceover-driven explainer videos — word-level voiceover sync, 109 motion recipe cards, an anti-slideshow camera system, Remotion rendering.
Motion capture for any creature from one AI video: two cameras in one frame, a DINOv2 joint reader, the rig fitted in both views, a GLB out.
Translated🍟 Official McDonald's China MCP agent skill: orchestrates 35 atomic tools into 4 business flows — campaign push · collab watch · best-value ordering · group bill splitting. Prices are truly calculated with calculate-price, and orders must be confirmed a second time before placing. | McDonald's China MCP agent skill: campaigns, collab watch, best-value ordering, group bill splitting.
Pixel-art diorama playbook and Three.js code kit: research-first build workflow, locked camera, palette snap, ordered dither, inked contour, animated toy-scale cast, per-entity frame QA.
Photoreal Blender scenes from a one-paragraph brief, built by AI agents: image→3D props on fal, scripted layout, lighting, camera and grade.