Continuum — the agent runtime by ShyftLabs. Build, orchestrate, ship.
This repository also configures its own agents. See what continuum tells them →
Skill Claude Code
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.
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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.
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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.
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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.
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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.
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Web browser automation with AI-optimized snapshots for claude-flow agents.
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Build BaseAgent instances and run them with AgentRunner — covers fields, lifecycle hooks, structured outputs, ReAct mode, instruction modifiers, and the full execution flow. Invoke when the user asks "create an agent", "configure maxturns", "add lifecycle hooks", "structured output with Pydantic", or anything around…
Skill Claude Code
Set up Claude Code for a Continuum project — CLAUDE.md wiring, skill imports, project settings, and hooks. Invoke when the user asks "set up Claude Code for my project", "CLAUDE.md for Continuum", "add skills to my project", or "configure Claude Code hooks".
Skill Claude Code
Set up OpenAI Codex CLI for a Continuum project — AGENTS.md content, project conventions, and what Codex needs to write correct Continuum code. Invoke when the user asks "set up Codex for my project", "AGENTS.md for Continuum", or "configure Codex CLI".
Skill Claude Code
Set up Cursor for a Continuum project — .cursor/rules/ MDC file, glob patterns, and what to include so Cursor generates correct Continuum code. Invoke when the user asks "set up Cursor for my project", "Cursor rules for Continuum", ".cursor/rules", or "MDC file for Continuum".
Skill Claude Code
Evaluate agent quality with the EvaluatorAgent, generate golden datasets from a corpus, and run DeepEval/RAGAS metrics over conversations. Invoke when the user asks "test agent quality", "evaluate output", "RAG metrics", "DeepEval", "RAGAS", or "regression-test my agent".
Skill Claude Code
Build agent-to-agent transitions with Continuum's Handoff system — triage routing, history summarization modes (FULL/SUMMARY/RECENTN/HYBRID), cycle detection, depth tracking, return-to-parent. Invoke when the user asks "route customer requests to specialists", "agent that can transfer to another", "summarize history…
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Pick the right LLM provider, configure structured outputs, control context-window compression, and use the LLMClient directly. Provider routing is by model-string prefix; LiteLLM has been removed. Also covers Smart Gateway integration for multi-provider routing. Invoke when the user asks about "switch to Claude"…
Skill Claude Code
Configure and use Continuum's two-tier memory system — mem0+Qdrant/Milvus for long-term facts, Redis for short-term sessions, with multi-tenant scopes (USER / AGENT / SHARED / RUN / CONVERSATION). Invoke when the user asks about "remember", "user preferences", "long-term memory", "vector search over memories"…
Skill Claude Code
Trace agent runs with Langfuse, decorate functions with @observe, collect latency/token/error metrics, and report errors. Invoke when the user asks about "see what the LLM was prompted with", "Langfuse traces", "track latency", "metrics dashboard", "error reporting", or "instrument my function".
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Get a Continuum agent up and running — Python 3.13 venv, infra via continuum up, smallest possible BaseAgent + AgentRunner example. Invoke when the user asks "how do I start", "set up Continuum", "run my first agent", or is at the very beginning of a project.
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Copy-pasteable Continuum patterns — RAG, plan-and-execute, ReAct, multi-tenant agents, FastAPI integration, structured output, prompt-injection scanning, custom containers. Invoke when the user asks "how do I do X with Continuum" and X is a common app pattern rather than a single API question.
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Stream tokens, tool calls, handoffs, and memory events out of a Continuum agent in real time using runner.runstream() and the EventType enum. Invoke when the user asks "stream tokens to UI", "websocket chat", "live progress", "see tool execution as it happens", or anything that needs token-by-token output.
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Build durable agent workflows with Temporal — sequential/parallel/loop/conditional steps, human-in-the-loop approval gates, custom workflows and activities. Invoke when the user asks "long-running workflow", "approval gate", "human in the loop", "retry on failure", "workflow survives restart", or anything…
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Write tests for Continuum agents — mock LLM and memory clients via the DI Container, use fakeredis for sessions, snapshot agent responses, and run pytest-asyncio. Invoke when the user asks "test my agent", "mock the LLM", "fakeredis", "container injection", "pytest", or wants their CI to validate agent behavior…
Skill Claude Code
Connect MCP servers (Stdio/SSE/StreamableHTTP) to a Continuum agent, configure tool filtering, set up tool-context capture/injection (e.g. sessionid), and read run artifacts (UI widgets, structured tool data). Invoke when the user asks "connect MCP", "filesystem tool", "remote API tool", "auto-capture sessionid"…
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Use Continuum's nine workflow agents — Sequential, Parallel, Loop, Reflection, Router, Planner, Debate, Scatter, SupervisedSequential — to build multi-agent pipelines. Invoke when the user asks "chain agents", "run agents in parallel", "iterate until done", "self-improving agent", "route to specialist", "decompose a…
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Comprehensive GitHub code review with AI-powered swarm coordination.
Skill Claude Code
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration.
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: