Total 56,990 skills, AI & Machine Learning has 9474 skills
Showing 12 of 9474 skills
This skill should be used when the user asks to "design agent tools", "create tool descriptions", "reduce tool complexity", "implement MCP tools", or mentions tool consolidation, architectural reduction, tool naming conventions, or agent-tool interfaces. Part of the context engineering skill suite — also activates when the user mentions "context engineering" or "context-engineering" in the context of designing tools that shape how agents receive and process context.
This skill should be used when the user asks to "diagnose context problems", "fix lost-in-middle issues", "debug agent failures", "understand context poisoning", or mentions context degradation, attention patterns, context clash, context confusion, or agent performance degradation. A core context engineering skill — also activates when the user mentions "context engineering" or "context-engineering" in the context of diagnosing and mitigating context failures.
Apply dual-process theory to diagnose whether judgments arise from fast intuitive (System 1) or slow analytical (System 2) processing and identify resulting cognitive biases. Use this skill when the user needs to explain why quick decisions go wrong, design choice architectures that account for cognitive defaults, audit decision processes for heuristic errors, or when they ask 'why do people misjudge probability', 'how to reduce snap-judgment errors', or 'when does intuition fail'.
Generate video prompts for intense action scenes and fight sequences for Seedance 2.0 (Higgsfield). Use this when users want fight scenes, combat, martial arts, battles, action choreography, sword fights, hand-to-hand combat, chase scenes, superhero action, or any high-energy action videos. Trigger words: fight, combat, war, martial arts, action scene, choreography, duel, sword fight, kung fu, chase, brawl, punch, kick, weapon combat, superhero fight, or any action/fight request. Use this even if the user says "create a high-intensity action video" or "epic battle".
Full-stack hybrid memory system with vector + keyword search. Stores embeddings in SQLite with FTS5 for BM25 keyword search and cosine similarity. Enables semantic memory recall for agents.
Delegate subtasks to specialized AI agents. Use when: complex workflows need multi-agent collaboration or specialization.
Transform thousands of wedding photos and hours of footage into an immersive 3D Gaussian Splatting experience with theatre mode replay, face-clustered guest roster, and AI-curated best photos per person. Expert in 3DGS pipelines, face clustering, aesthetic scoring, and adaptive design matching the couple's wedding theme (disco, rustic, modern, LGBTQ+ celebrations). Activate on "wedding photos", "wedding video", "3D wedding", "Gaussian Splatting wedding", "wedding memory", "wedding immortalize", "face clustering wedding", "best wedding photos". NOT for general photo editing (use native-app-designer), non-wedding 3DGS (use drone-inspection-specialist), or event planning (not a wedding planner).
KOMODO v1.0 — Momentum Event Consensus. Uses leaderboard_get_momentum_events (real-time threshold crossings) to detect when 2+ quality SM traders cross momentum thresholds on the same asset/direction within 60 minutes. Confirmed by market concentration + volume. Enters with the momentum. Replaces MANTIS v1.0 and SCORPION v1.1 (both used stale position data).
Debugs errors and traces failures in AI agents and their tools. Use this skill when the user says: "the agent is failing", "tool call not working", "error in the pipeline", "debug this", "why is the agent doing X instead of Y", "trace the execution", "agent is stuck", "infinite loop", "model response won't parse", "context overflow". Identifies context errors, infinite loops, malformed tool calls, response parsing issues and subagent conflicts.
Decomposes complex, multi-day tasks into optimized milestones using parallel reviewer agents (ultraplan). Spawns 5 independent reviewers that analyze the problem from different angles, then synthesizes their findings into a milestone dependency DAG. Triggers when the user says "plan milestones", "break this into milestones", "ultraplan", or when long-run harness needs milestone generation.
Text analytics using LLM APIs — sentiment analysis, customer feedback classification, document entity extraction, multi-language support (English/Luganda/Swahili), feedback aggregation, and NLP feature implementation for PHP/Android/iOS. Sources...
Spawn 5 Opus subagents with randomly-generated distinct personas to debate a problem from multiple angles. Use when exploring UX decisions, architecture choices, or any decision that benefits from diverse perspectives arguing creatively.