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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".
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
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.
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".
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".
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 max_turns", "add lifecycle hooks", "structured output with Pydantic", or anything around the core agent abstraction.
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", "Gemini structured output", "context length error", "rate limiting", "JSON schema", "Smart Gateway", "gateway_mode", or "how does the LLM client work".
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", "multi-tenant isolation", "PII filtering on memory writes", "Milvus", "Qdrant", or memory-related errors.
| name | continuum-codex |
| description | 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". |
Codex CLI reads AGENTS.md from the project root automatically.
The Continuum repo ships a ready-made AGENTS.md — copy or symlink
it into any downstream project.
# My Project — Agent Knowledge Pack
@/path/to/continuum/AGENTS.md
## Project-specific conventions
- Package: `my_app` (imports as `from my_app import ...`)
- Entry point: `src/my_app/main.py`
- Agents are defined in `src/my_app/agents.py`
- Tests: `pytest tests/` with `pytest-asyncio`
## Key agents in this project
| Agent | File | Purpose |
|---|---|---|
| `SupportAgent` | `agents/support.py` | Customer support triage |
| `BillingAgent` | `agents/billing.py` | Billing inquiries |
The @import pulls in the full Continuum API reference so Codex knows
every class, field, and pattern.
Codex needs these facts to write correct code on the first try:
orchestrator (not continuum or shyftlabs_continuum)asyncio.run()SMART_GATEWAY_URL:6380, Milvus/Qdrant for memoryMinimal addition to any AGENTS.md:
## Continuum conventions
- Import: `from orchestrator.agent import BaseAgent, AgentRunner`
- All APIs async. Use `asyncio.run(main())` at entrypoints.
- Model routing: prefix-based (`gpt-*` → OpenAI, `claude-*` → Anthropic, `gemini/*` → Gemini)
- Gateway: set `SMART_GATEWAY_URL` to route all models through the Smart Gateway
- Memory: Redis (:6380) for sessions, Milvus (:19530) or Qdrant (:6333) for long-term
- Load dotenv: always `load_dotenv()` before importing orchestrator settings
# Point Codex at the project
cd my-continuum-project
codex "add a handoff from SupportAgent to BillingAgent for billing questions"
Codex will read AGENTS.md, understand the Continuum API, and generate
correct Handoff(target_agent=..., description=...) code.
load_dotenv() — Codex-generated scripts often miss it and settings fail to load.litellm — it's removed from Continuum.AGENTS.md present so it reads the authoritative API.