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agent-memory-systems
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them.
agent-memory-systems
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them.
conversation-memory
Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory
memory-systems
Design short-term, long-term, and graph-based memory architectures. Use when building agents that must persist across sessions, needing to maintain entity consistency across conversations, or implementing reasoning over accumulated knowledge.
demand-sensing-integrator
Real-time demand signal integration from POS, channel data, and external signals for short-term forecast enhancement
pulumi-esc
Guidance for working with Pulumi ESC (Environments, Secrets, and Configuration). Use when users ask about managing secrets, configuration, environments, short-term credentials, configuring OIDC for AWS, Azure, GCP, integrating with secret stores (AWS Secrets Manager, Azure Key Vault, HashiCorp Vault, 1Password), or using ESC with Pulumi stacks.
conversation-memory
ALWAYS use this when the request matches Conversation Memory: Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory
memory-systems
ALWAYS use this when the request matches Memory Systems: Design short-term, long-term, and graph-based memory architectures.
memory-design
Design memory for an LLM agent — what to keep, where to keep it, and when memory hurts more than it helps. Use when the user is adding memory to an agent and mentions short-term memory, long-term memory, episodic, semantic, conversation history, summary memory, vector memory, memory store, mem0, Letta, MemGPT, or asks "should this agent remember?" / "why is…
llm-agent-orchestration
Build and orchestrate LLM-powered agents. Covers agent architectures (ReAct, Plan-and-Execute, multi-agent), tool use and function calling, LangChain agents, LangGraph workflows, CrewAI multi-agent systems, Autogen, agent memory (short-term, long-term, episodic), agent planning and reasoning, error handling and recovery, agent evaluation and testing, human-…
bedrock-agentcore-memory
Amazon Bedrock AgentCore Memory for persistent agent knowledge across sessions. Episodic memory for learning from interactions, short-term for session context. Use when building agents that remember user preferences, learn from conversations, or maintain context across sessions.
grad-ambidexterity
Apply organizational ambidexterity theory to balance exploration and exploitation activities. Use this skill when the user needs to diagnose whether an organization is over-exploiting or over-exploring, design structures that support both innovation and efficiency, or evaluate the tension between short-term performance and long-term renewal.
polymarket-fast-loop
Trade Polymarket BTC 5-minute and 15-minute fast markets using CEX price momentum signals via Simmer API. Default signal is Binance BTC/USDT klines. Use when user wants to trade sprint/fast markets, automate short-term crypto trading, or use CEX momentum as a Polymarket signal.
agent-memory-systems
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you c…
conversation-memory
Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory Use when: conversation memory, remember, memory persistence, long-term memory, chat history.
memory-systems
Design short-term, long-term, and graph-based memory architectures
10000-year-clock
Think at civilization-scale timeframes by asking how decisions look over 10,000 years, countering short-term pathological thinking
advanced-short-term-actuarial-mathematics
Guides advanced short-term actuarial mathematics aligned with SOA ASTAM and P&C/health-adjacent modeling—severity and frequency distributions, aggregate and compound loss models, Bühlmann and Bühlmann-Straub credibility, ratemaking and experience rating, short-term reserving at the math level, MLE and goodness-of-fit, and risk measures (VaR, TVaR). Tool-agn…
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