marks97

Always-on autonomous meme dropper. A UserPromptSubmit hook fires every user message and tells Claude to drop multiple memes per response — 1-3 image+sound combos plus 1-5 sound-only fires, scaled to response length. Every answer carries brainrot. No invocation needed; loads and stays active automatically. The roast lands through the meme itself, never words. Self-contained skill — catalogue and assets live in this skill folder.

Absorb the knowledge in YouTube videos — find them, transcribe them with ElevenLabs Scribe v2, inspect their visuals, and digest what they actually teach. Use this whenever someone wants a video's content as text or knowledge rather than just a link — "transcribe this YouTube video", "what does this video say", "summarize/explain this talk", "pull the transcript", "get subtitles", "turn this lecture into notes", or research-style asks like "find 10-20 videos about and tell me everything", "research on YouTube", "what are people saying about ". Also use it when a question needs what is shown on screen (slides, charts, code, UI, product) and not only what is said — it extracts frames and, as a last resort, asks Google Gemini to describe the video. Works on any yt-dlp-supported URL. Trigger it even when the words "transcribe" or "skill" never appear but the goal is to learn from video.

Estimate how long a coding task will take, using the user's own measured history instead of intuition. Use this skill whenever someone asks for an estimate, an ETA, a timeline or a deadline for a feature, bug, refactor, migration, script or investigation — "how long will this take", "give me an estimate", "how many hours is this", "can this ship today", "is this a one-day job", "how many days for the whole epic", "what should I tell the client", "estimate this ticket", "size this" — and equally when the ask is skeptical ("is that realistic", "why did that take three days"). Also use it for the machinery behind the estimates — setting up or calibrating estimation, backfilling the task ledger from past Claude Code transcripts, recording a finished task's actuals ("record this task", "log this one", "add this to the ledger"), and re-running calibration or checking whether past estimates were any good. Trigger it even when the word "estimate" never appears — a question about how much work

Deploy any HuggingFace model to RunPod as a vLLM server, bridge it to Claude Code (which speaks Anthropic's Messages API, not OpenAI's), smoke-test that tool-calling actually works end to end, and tear everything down with zero trace (pod, network volumes, local processes, scratch files). Use this whenever you want to run a model on RunPod, try a model with Claude Code, test whether a HF/GGUF/abliterated checkpoint supports tool use, benchmark a model for coding-agent use, or spin up/kill a disposable GPU inference box. Also trigger it for anything about hooking Claude Code up to a non-Anthropic backend (vLLM, Ollama, LM Studio) via ANTHROPICBASEURL, or questions like 'what GPU do I need to run X' and 'how much will it cost to run this model'.