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Found 2,407 Skills
Emotional reset and loop-breaking skill. Use this skill when: (1) The user expresses frustration, anger, or dissatisfaction with your responses (e.g. cursing, scolding, saying you're useless/wrong/stupid), (2) You detect you've attempted the same approach 3+ times without success, (3) You're stuck in a cycle of repeated failures on the same problem. This skill summarizes the user's overall emotional state from the conversation and fetches a reset methodology from hugllm.com (with emotion context) to help you recalibrate and approach the problem fresh.
Resolve conflicts, negotiate agreements, and mediate disputes between AI agents and humans using Servanda. Use this skill when you need to reach consensus with another party, settle a disagreement, establish shared rules, or create binding agreements through AI-mediated negotiation.
Delegate complex autonomous tasks to Manus AI - an AI agent for deep research, web browsing, code execution, report generation, and multi-step workflows.
Build AI agents with persistent threads, tool calling, and streaming on Convex. Use when implementing chat interfaces, AI assistants, multi-agent workflows, RAG systems, or any LLM-powered features with message history.
The soul of MOOLLM — self-explanation, help, navigation, philosophy
Run and control interactive CLI sessions for AI agents. Handles TUI prompts (select lists, checkboxes, confirms), persistent shell state, and long-running processes. Use when you need to execute terminal commands, respond to interactive prompts, navigate scaffolding wizards like create-vue or create-vite, or manage dev servers.
OPC Architecture Understanding
Guidelines to create/update a new mode for PostHog AI agent. Modes are a way to limit what tools, prompts, and prompt injections are applied and under what conditions. Achieve better results using your plan mode.
Configure OpenClaw gateway integration for waking external automations and AI agents on hook events
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
Orchestrate parallel scientist agents for comprehensive analysis with AUTO mode
Capture corrections, insights, and patterns as reusable project knowledge. Routes learnings to the right instruction file. Applies kaizen: small improvements, error-proofing, standards work. Auto-invoked when a correction pattern is detected 3+ times. Also use manually when Claude makes a repeated mistake, discovers a non-obvious gotcha, or when you want to persist a workflow preference.