搜索「Agent Memory」的结果

io.github.ruvnet/ruflo/agent-release-manager

Agent skill for release-manager - invoke with $agent-release-manager

io.github.ruvnet/ruflo/agent-quorum-manager

Agent skill for quorum-manager - invoke with $agent-quorum-manager

io.github.ruvnet/ruflo/agent-performance-monitor

Agent skill for performance-monitor - invoke with $agent-performance-monitor

io.github.ruvnet/ruflo/agent-pagerank-analyzer

Agent skill for pagerank-analyzer - invoke with $agent-pagerank-analyzer

io.github.ruvnet/ruflo/agent-issue-tracker

Agent skill for issue-tracker - invoke with $agent-issue-tracker

io.github.ruvnet/ruflo/agent-gossip-coordinator

Agent skill for gossip-coordinator - invoke with $agent-gossip-coordinator

io.github.ruvnet/ruflo/agent-github-modes

Agent skill for github-modes - invoke with $agent-github-modes

io.github.ruvnet/ruflo/agent-dev-backend-api

Agent skill for dev-backend-api - invoke with $agent-dev-backend-api

io.github.ruvnet/ruflo/agent-challenges

Agent skill for challenges - invoke with $agent-challenges

io.github.ruvnet/ruflo/agent-byzantine-coordinator

Agent skill for byzantine-coordinator - invoke with $agent-byzantine-coordinator

io.github.ruvnet/ruflo/reasoningbank-agentdb

Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.

io.github.ruvnet/ruflo/agent-coordination

Agent spawning, lifecycle management, and coordination patterns. Manages 60+ agent types with specialized capabilities. Use when: spawning agents, coordinating multi-agent tasks, managing agent pools. Skip when: single-agent work, no coordination needed.

io.github.exceptionless/Exceptionless/agent-browser

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.

io.github.JimmyLv/BibiGPT-v1/agent-browser

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.

io.github.davila7/claude-code-templates/agent-md-refactor

Refactor bloated AGENTS.md, CLAUDE.md, or similar agent instruction files to follow progressive disclosure principles. Splits monolithic files into organized, linked documentation.

io.github.softaworks/agent-toolkit/agent-md-refactor

Refactor bloated AGENTS.md, CLAUDE.md, or similar agent instruction files to follow progressive disclosure principles. Splits monolithic files into organized, linked documentation.

io.github.ruvnet/RuView/v3-memory-unification

Unify 6+ memory systems into AgentDB with HNSW indexing for 150x-12,500x search improvements. Implements ADR-006 (Unified Memory Service) and ADR-009 (Hybrid Memory Backend).

io.github.ruvnet/RuView/reasoningbank-agentdb

Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.

io.github.ruvnet/RuView/agentdb-vector-search

Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.

io.github.ruvnet/RuView/agentdb-optimization

Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.

io.github.ruvnet/RuView/agentdb-memory-patterns

Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.

io.github.ruvnet/RuView/agentdb-learning

Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.

io.github.ruvnet/RuView/agentdb-advanced

Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

io.github.YPares/agent-skills/cursor-agent-supervisor

Offloading tasks with a well-defined scope to sub-agents, for instance to use a sub-agent to implement a set of specs. Use this skill whenever a task should not need a broad knowledge of the whole project