Second-by-second retention forecast for your video's first 6 seconds — which seconds bleed, why, and 3 ranked hook fixes. Every prediction goes on an auditable ledger.
Turn long-form content into smarter short-form opportunities.
Open-source CLI (MIT, 2k+ GitHub stars, Hacker News front page). Turn any video URL or local file into scene-aware keyframes plus a timestamped, speaker-labeled transcript your LLM can actually read. - Runs 100% on your machine, nothing is uploaded - Works with Claude, ChatGPT, Gemini or local models - URL videos reuse the platform's own captions, Whisper otherwise New in 0.10.5: Apple Silicon GPU transcription, about 6x faster on M-series Macs, same no-fake-captions gate.
Upload your finished Short, Reel, or TikTok. Get timestamped checks and fixes for captions, on-screen text, and visual mistakes before you publish.
Independent tool summarizing selected public Bitcoin and macro commentary attributed to Lyn Alden. Reports show dates and original links when available. AI interpretation is separately labeled and may be inaccurate. It does not trade, access financial accounts, or provide personalized recommendations. Not affiliated with, authorized by, sponsored by, or endorsed by Lyn Alden or Lyn Alden Investment Strategy. For informational and educational purposes only—not investment advice.
Organize user-provided broker screenshots, statements, and CSV data into a multi-account reconciliation report with cash, positions, transfers, option coverage, and clearly marked missing or estimated values.
“Turn one idea into a production-ready Short with a final script, exact shot timing, storyboards, generator-ready visual prompts, captions, titles, and A/B variants.”
Type any US ticker for a 30-second read: valuation vs its own history, growth, quality, technical structure, earnings catalyst, plus a 12-month momentum rank and a daily market dashboard. A reading engine — not investment advice.
Structure project docs as modular memory + reasoning files so AI agents load only what they need — cutting token usage by 70–96% per query. Grounded in Anthropic, LangChain, and Crawl4AI's production llm.txt research. Implements write/select/compress/isolate context engineering strategies.