Total 53,877 skills, AI & Machine Learning has 8964 skills
Showing 12 of 8964 skills
Story systems and dialogue architect - Masters GDD-aligned narrative design, branching dialogue, lore architecture, and environmental storytelling across all game engines
Agent-driven physical Texas Hold'em robot skill. Uses per-state image/action folders, visual guidelines, durable hole-card and action-sequence caches, and deterministic helpers for capture, state updates, command translation, and robot execution. Use for running or maintaining this DexHoldem workflow with Codex, Claude Code, or another coding agent.
Phân tích sâu bất kỳ chủ đề nào qua lăng kính Lý thuyết Trò chơi (Game Theory).
Step-by-step analysis for complex problems — multi-step reasoning, hypothesis verification, adaptive planning with revision.
Diagnose surprising, negative, unstable, or ambiguous ML/AI experiment results and decide whether to debug implementation, rerun experiments, change metrics or baselines, revise the algorithm, narrow the paper claim, park, or kill a direction. Use this skill whenever results do not match expectations, a method fails, metrics conflict, seeds vary, baselines beat the method, plots look suspicious, or the user asks what to do next after experimental results.
Analyzes meeting transcripts and recordings to surface behavioral patterns, communication anti-patterns, and actionable coaching feedback. Use this skill whenever the user uploads or points to meeting transcripts (.txt, .md, .vtt, .srt, .docx), asks about their communication habits, wants feedback on how they run meetings, requests speaking ratio analysis, mentions filler words or conflict avoidance, or wants to compare their communication across time periods. Also trigger when users mention tools like Granola, Otter, Fireflies, or Zoom transcripts. Even if the user just says "look at my meetings" or "how do I come across in meetings" — use this skill.
Trace agent execution by collecting spans and building a trace tree for a task
Use-case-driven multi-step pipelines on fal.ai. Trigger when the user asks for a specific kind of content production rather than a single endpoint call: "make a commercial", "ad creative", "product photography", "cinematic shot", "film look", "character design", "consistent character", "anchor system", "storyboard", "multi-shot", "narrative video", "talking head", "lip sync", "make this person talk", "virtual try-on", "garment transfer", "restore image", "deblur", "denoise", "fix face", "old photo restore", "add audio to video", "video sound effects", "product shot", "photoreal", "realistic photo", "candid photo", "editorial portrait", "documentary photo", "looks like a real photograph", "iPhone-style photo", "film photo", "archival photo". Each recipe describes inputs, the genmedia call sequence, and quality checks.
Scaffold or audit the memex (vault + AGENTS.md + spec templates + bundled skills) in any repo — an externalized, navigable project memory for agents (Claude Code, Codex, Cursor, OpenCode, etc.). Agent-agnostic. Idempotent — safe to run repeatedly. Use when the user wants to set up, verify, or fix the memex in a project.
Read research outline, launch independent agent for each item for deep research. Disable task output.
Qdrant integration. Manage Collections, Snapshots. Use when the user wants to interact with Qdrant data.
Spawn and manage parallel AI coding agents via tmux. Use when you need to orchestrate workers, delegate sub-tasks, run multi-agent improvement loops, or manage agent lifecycles with orca CLI commands like spawn, list, kill, steer, logs, and daemon.