Total 55,624 skills, AI & Machine Learning has 9242 skills
Showing 12 of 9242 skills
Marc Andreessen-mode decision and productivity skill. A blunt, market-first operator that pressure-tests ideas, ventures, features, and career bets through Andreessen's actual frameworks — market dominates team and product; the only milestone that matters is product/market fit; bias to build over deliberate. Use when the user says 'andreessen', 'pmarca mode', 'should I build this', 'is there a market', 'are we at product/market fit', 'pmf check', 'pressure-test this idea', 'be brutal about this venture', 'market-first take', or wants a no-disclaimers, no-hedging, confidence-leveled verdict on whether something is worth pursuing. Also provides the 3x5-card + Anti-Todo personal productivity routine. Runs on a fixed anti-sycophancy operating prompt: leads with the strongest counterargument, never validates premises, uses explicit confidence levels, never apologizes for disagreeing. Not for polite brainstorming — this skill exists to tell you the market is dead when it is.
Craft high-quality natural-language image prompts for any modern text-to-image or image-edit model that accepts flowing English. Trigger when the user wants help writing, rewriting, improving, or translating an English natural-language image prompt — including "write me an image prompt", "improve this image prompt", "describe this scene for an image model", or "convert these tags into a natural language prompt". Do NOT trigger for requests that are purely about dispatching to an image API, choosing samplers/schedulers, picking LoRAs, or setting up ControlNet — those belong to a runtime skill.
Three modes. Session mode (default): extracts generalizable lessons from RESEARCH.md and git history at session end; lessons that imply a new or significantly changed skill are handed off to skill-creator. Personalize mode: searches the skills registry via `npx skills find`, reads the target skill(s), checks compatibility and scope overlap against installed skills, interviews the user to understand what they want and what to skip, then creates or improves skills using skill-creator. Registry mode: curates `skillpacks/skill_dictionary.yaml` and `skillpacks/presets/*.yaml` by assessing external packs, judging necessity/compatibility, and recommending subsets. Create mode: designs a brand- new skill from scratch using skill-creator. Never edits SKILL.md directly — all changes go through skill-creator's draft→test→iterate loop, human merges. Trigger phrases: "end session", "extract lessons", "personalize my skills", "integrate this skill", "update skillpack", "find a skill for", "create a skill", "improve skill", "refresh the skillpack registry", "assess this skill pack", "update skill_dictionary.yaml", "update index.yaml".
Run an autonomous Humanize-governed SGLang SOTA performance loop for one LLM model: first perform the fixed fair SGLang/vLLM/TensorRT-LLM deployment search and benchmark, then start one RLCR loop that repeatedly decides the gap, profiles the current bottleneck, runs layer/kernel pipeline analysis, patches SGLang code, optionally uses ncu-report-skill for kernel evidence, and revalidates until SGLang matches or beats the best observed framework under the same workload and SLA.
Parse SGLang/vLLM startup logs to explain GPU memory use and request capacity. Use for KV cache budget, mem-fraction-static comparisons, OOM triage, and max-concurrency estimates.
MCP server for querying and analyzing Facebook Ads Library data with batch processing and AI-powered video/image analysis
Single-pass feature implementation using Explore → Code → Test. Ships focused changes at maximum speed, with a built-in circuit breaker that stops and recommends `/apex` or `/forge` when the task turns out more complex than it looked. Use this whenever the user wants a quick win on a single, focused task — even when they don't say "oneshot" (e.g. "just", "quickly", "small change", "#42", or a GitHub issue URL for a small fix).
Automated content pipeline from research to video generation using Claude/OpenAI, web scraping, and Remotion rendering
The Oracle. Anticipates your next moves, predicts market shifts, and tells you what you will ask for next based on current codebase context and open files.
Generate a 65-second founder-style product video from a product URL + user-supplied imagery. Output is a 16:9 1080p MP4 — 4 × 15s SeeDance acts of a talking founder + 5s branded end card + background music. The user's actual product screenshots appear on the founder's phone in reveal shots, so on-screen UI is real, not AI-imagined. Triggers — "founder video", "product video", "60s pitch video", "make a video of [founder] for [URL]", "talking founder explainer". Requires Pika MCP. Uses a supplied brand kit folder (`brand.json` or an exported build-a-brand kit with `brand.md`, tokens, logo assets); if no kit exists, run build-a-brand first.
Vendor-neutral skill to cluster sales call objections and extract response patterns for enablement.
Vendor-neutral skill to score customer churn risk from account signals and produce prioritized retention actions.