agentdb-advanced
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems…
Run a historical backtest using npx neural-trader with Rust/NAPI engine (8-19x faster) and walk-forward validation; Ed25519-sign the result for paper→live tamper evidence (ADR-126 Phase 4)
$ npx -y skills add ruvnet/ruflo --skill trader-backtest --agent claude-codeHow it fires
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/trader-backtestContext preview
The summary Claude sees to decide when to auto-load this skill.
Run a historical backtest using npx neural-trader with Rust/NAPI engine (8-19x faster) and walk-forward validation; Ed25519-sign the result for paper→live tamper evidence (ADR-126 Phase 4)
name: trader-backtest description: Run a historical backtest using npx neural-trader with Rust/NAPI engine (8-19x faster) and walk-forward validation; Ed25519-sign the result for paper→live tamper evidence (ADR-126 Phase 4) allowed-tools: Bash Read mcp__plugin_ruflo-core_ruflo__memory_store mcp__plugin_ruflo-core_ruflo__memory_retrieve mcp__plugin_ruflo-core_ruflo__memory_search mcp__plugin_ruflo-core_ruflo__memory_delete mcp__plugin_ruflo-core_ruflo__neural_train mcp__plugin_ruflo-core_ruflo__agentdb_pattern-store argument-hint: "<strategy-name> --symbol <TICKER> [--period 2020-2024]"
Run a historical backtest using the `neural-trader` Rust/NAPI engine, then Ed25519-sign the result so the paper→live promotion gate has cryptographic tamper evidence (ADR-126 Phase 4 + CWE-347 pattern).
Steps: 1. Ensure neural-trader is available: `npm ls neural-trader 2>/dev/null || npm install --ignore-scripts neural-trader` 2. Check for saved strategy config: `mcp__plugin_ruflo-core_ruflo__memory_retrieve({ key: "strategy-STRATEGY_NAME", namespace: "trading-strategies" })` If not found, list available: `mcp__plugin_ruflo-core_ruflo__memory_search({ query: "strategy", namespace: "trading-strategies", limit: 10 })` 3. Run backtest via neural-trader CLI:
npx neural-trader --backtest --strategy <name> --symbol <TICKER> --period <range> --walk-forward
For multi-indicator strategies:
npx neural-trader --backtest --strategy multi-indicator --position-sizing kelly --symbol SPY --period 2020-2024
4. Capture performance metrics from output: total return, annualized return, Sharpe ratio, Sortino ratio, max drawdown, win rate, profit factor, number of trades. 5. Dedup prior backtests for the same `(strategyId, paramsHash)` before storing the fresh one (ADR-125 lifecycle / ADR-126 Phase 2 — `keep-newest` semantics):
6. **Sign the artifact (ADR-126 Phase 4):**
1. `RUFLO_WITNESS_KEY_PATH` env var — points to a JSON file with `{ "privateKey": "<hex>" }`. 2. `verification/witness-key.json` (the ADR-103 default path, if present).
7. **Store the (possibly signed) artifact** to the canonical `trading-backtests` namespace: `mcp__plugin_ruflo-core_ruflo__memory_store({ key: "backtest-STRATEGY-TIMESTAMP", value: JSON.stringify(signedArtifact), namespace: "trading-backtests" })` The stored value contains `witnessSignature` + `witnessPublicKey` when signed; downstream consumers (`trader-cloud-backtest`) MUST call `verifyBacktestArtifact(artifact, trustedPublicKey)` before promoting any artifact to live. 8. If Sharpe > 1.5, store as successful pattern: `mcp__plugin_ruflo-core_ruflo__agentdb_pattern-store({ pattern: "profitable-STRATEGY_TYPE", data: "PARAMS_AND_RESULTS" })` 9. Train SONA on the outcome: `mcp__plugin_ruflo-core_ruflo__neural_train({ patternType: "trading-strategy", epochs: 10 })`
An agent meta-harness for Claude Code and Codex. 📖 RuFlo Explained — Build an AI Team That Plans, Remembers, Tests, and Improves A 14-chapter guide: from the basic idea to a first useful task, then memory, agent teams, plugins, cost and verification.
Repo: ruvnet/ruflo
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