trader-cloud-backtest
Run a heavy neural-trader job (long walk-forward, big Monte-Carlo, parameter sweep, model training) on the Anthropic Managed Agent cloud runtime instead of locally
Profile →npx skills add ruvnet/ruflo --skill trader-cloud-backtest --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Cloud backtest / train (neural-trader on a Managed Agent) Dispatch a **heavy** `neural-trader` job to an Anthropic Claude Managed Agent (cloud container) instead of running it locally. See project ADR-117 (recipe + cost rules) and ADR-115 (the `managed_agent_*` runtime). ## When to use this vs `trader-backtest` (local) | Job | Runtime | |---|---| | Quick sanity check; one short backtest (< ~1 min) | local — use the `trader-backtest` skill | | Multi-year **walk-forward**, big **Monte-Carlo** count, **parameter sweep** over a grid, or **model training** (LSTM/Transformer/N-BEATS) | **cloud — this skill** | Prereq: `ANTHROPIC_API_KEY` (or `CLAUDE_API_KEY`) + Managed Agents beta access. If `managed_agent_*` returns "needs ANTHROPIC_API_KEY", fall back to the local `trader-backtest` skill. ## Steps 1. **Estimate first.** From the job size, print an estimated cost (≈ container-minutes × rate + tokens) — a long sweep is a deliberate choice, not a default. 2. **Provision (or reuse) the container** — install neural-trader at container start so the agent doesn't reinstall mid-run: ``` managed_agent_create({ name: "nt-cloud", model: "claude-haiku-4-5-20251001", // orchestration only — the c
- When to use this vs trader-backtest (local)
- Steps
- Cost rules (don't skip)
- Quick example
What does the trader-cloud-backtest skill do?
Run a heavy neural-trader job (long walk-forward, big Monte-Carlo, parameter sweep, model training) on the Anthropic Managed Agent cloud runtime instead of locally
How do I install it?
Run `npx skills add ruvnet/ruflo --skill trader-cloud-backtest --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ruvnet/ruflo, a repository with 67,015 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.