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Found 1,678 Skills
Project setup wizard for AI agents. Use when user requests setup or when .agents/CONTEXT.md is missing or incomplete and setup recovery is needed. Generates .agents/CONTEXT.md with stack, structure, coding rules, and skill mapping.
AI agent operational rules including token discipline, navigation-first approach, and output contracts. Use when you need efficient and predictable agent behavior during development tasks.
Working memory management, context prioritization, and knowledge retention patterns for AI agents. Use when you need to maintain relevant context and avoid information loss during long tasks.
Enter the Gigaverse as an AI agent. Create a wallet, quest through dungeons, battle echoes, and earn rewards. The dungeon awaits.
Interactive onboarding for new AgentOps users. Guided RPI cycle on your actual codebase in under 10 minutes. Triggers: "quickstart", "get started", "onboarding", "how do I start".
Knowledge flywheel health monitoring. Checks velocity, pool depths, staleness. Triggers: "flywheel status", "knowledge health", "is knowledge compounding".
This skill should be used when the user asks to "track issues", "create beads issue", "show blockers", "what's ready to work on", "beads routing", "prefix routing", "cross-rig beads", "BEADS_DIR", "two-level beads", "town vs rig beads", "slingable beads", or needs guidance on git-based issue tracking with the bd CLI.
Systematically debug issues, investigating bugs, troubleshooting problems, or tracking down errors with persistent state across context resets. Triggers include "debug", "investigate bug", "troubleshoot", "find the problem", "why isn't this working", and "debug session".
Comprehensive cryptocurrency market research and analysis using specialized AI agents. Analyzes market data, price trends, news sentiment, technical indicators, macro correlations, and investment opportunities. Use when researching cryptocurrencies, analyzing crypto markets, evaluating digital assets, or investigating blockchain projects like Bitcoin, Ethereum, Solana, etc.
Integrate Honcho memory and social cognition into existing Python or TypeScript codebases. Use when adding Honcho SDK, setting up peers, configuring sessions, or implementing the dialectic chat endpoint for AI agents.
Generate structured session summaries optimized for future AI agent consumption. Use when (1) ending a coding/debugging session, (2) user says "compact", "summarize session", "save context", or "wrap up", (3) context window is getting long and continuity matters, (4) before switching tasks or taking a break. Produces machine-readable handoff documents that let the next session start fluently without re-explaining.
Instructions for AI agents to create new skills and add them to the skills repository