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trader-backtest

Test trading strategies against historical market data and collect performance metrics. The skill checks whether data is real or synthetic and can digitally sign results to help detect tampering before a strategy moves into live trading.

OriginalShow the original 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)

AI rating70/ 100See how to install

Good for

  • Evaluate a strategy against historical market data
  • Compare returns, risk measures, and trading results
  • Prepare signed backtest results for live-trading review
  • Check whether a backtest used synthetic data

Overview

What it does

trader-backtest tests trading strategies against historical market data to assess returns and risk. It uses the Rust/NAPI engine in neural-trader for walk-forward validation, shifting the test period forward in sequence. It collects returns, Sharpe ratio, maximum drawdown, win rate, and trade counts, then saves results while clearing older results for the same strategy and settings. Results based on real data receive an Ed25519 digital signature to help detect tampering.

When it helps

Use it to test a saved trading strategy or check the origin and integrity of backtest results before moving from paper trading to live trading. It inspects dataSource in the results to check for synthetic data.

Example requests

  • “Test this strategy using SPY data from 2020 through 2024.”
  • “Summarize returns, maximum drawdown, and win rate, then sign and save the results.”

Notes

Requires neural-trader and the related ruflo tools. Failed data retrieval falls back to synthetic data, so --live alone does not establish that real data was used. Results containing synthetic data are not signed for promotion to live trading. Without a signing key, results are saved unsigned and promotion to live trading is refused.

This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.

Objective evaluation

AI rated this skill on four points using only the contents of its SKILL.md. Stars and popularity are not taken into account.

Clear instructionsIs it clear when to use it and what it does?
AGoodThe skill explicitly describes historical strategy testing and signed results for promotion to live trading.
Concrete stepsAre steps, inputs, outputs, and examples spelled out?
AGoodExecution commands, data source checks, signed artifact fields, and the storage namespace are specified.
SafetyAre sending data, deleting files, and running commands disclosed?
CCheck firstIt deletes older results and reads a private signing key without a prior confirmation step.
Easy setupDoes it need few tools or API keys, and are they documented?
BPartly lackingInstallation of neural-trader and key generation are documented, but setup instructions for the related ruflo tools are absent.

The total counts each point as A = 25, B = 15, C = 5. Rated by AI (OpenAI Codex) as of Oct 21, 2026. Treat it as a guide and read the original before installing.

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Files included (1)

  • SKILL.md5.9 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

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 --live
    
    For multi-indicator strategies:
    npx neural-trader --backtest --strategy multi-indicator --position-sizing kelly --symbol SPY --period 2020-2024
    

3b. Check the data source. Without --live the backtest runs on synthetic bars, and when the live fetch fails it silently falls back to them. Read dataSource for every symbol in the result. Only yahoo-finance is real data. If any symbol is synthetic or mixed, store the result with synthetic: true in the body, do NOT sign it for paper→live promotion, and tell the user why. 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):

  • Search: mcp__plugin_ruflo-core_ruflo__memory_search({ query: "backtest STRATEGY paramsHash:PARAMS_HASH", namespace: "trading-backtests", limit: 10 })
  • For each hit whose key matches backtest-STRATEGY-* AND whose stored paramsHash equals the current run's hash, delete it: mcp__plugin_ruflo-core_ruflo__memory_delete({ key: "OLD_KEY", namespace: "trading-backtests" })
  • (Note: even without this proactive step, the MemoryConsolidator.dedup('keep-newest') background pass introduced in @claude-flow/memory@3.0.0-alpha.18 runs every 6h and will eventually converge. Doing it inline keeps memory_search results deterministic immediately after a re-run.)
  1. Sign the artifact (ADR-126 Phase 4):
    • Build the SignedBacktestArtifact body — { strategyId, paramsHash, dataRange: {from,to}, metrics, runsHash, generatedAt } — where paramsHash = sha256(canonical params JSON), runsHash = sha256(canonical runs array JSON), and generatedAt = new Date().toISOString().
    • Resolve the witness signing key. The skill reads the key path in this order; the FIRST that resolves wins:
      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).
    • If the key resolves: call signBacktestArtifact(body, privateKeyHex) from plugins/ruflo-neural-trader/src/signed-artifact.mjs. The returned value is a SignedBacktestArtifact with schema, witnessPublicKey: "ed25519:<hex>", and witnessSignature: "<hex>" populated.
    • If NEITHER path resolves: log a loud warning — "[WARN] ruflo-neural-trader: no witness signing key found (RUFLO_WITNESS_KEY_PATH unset, verification/witness-key.json missing) — storing backtest artifact in UNSIGNED degraded mode. paper→live promotion will be refused by trader-cloud-backtest until a signed artifact replaces this one." — and store the body unsigned. NEVER silently fall back.
  2. 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.
  3. If Sharpe > 1.5, store as successful pattern: mcp__plugin_ruflo-core_ruflo__agentdb_pattern-store({ pattern: "profitable-STRATEGY_TYPE: PARAMS_AND_RESULTS", type: "trading-strategy", confidence: 0.8 }) (the tool takes pattern, type, confidence; a data field is ignored)
  4. Train SONA on the outcome (skip for synthetic runs): mcp__plugin_ruflo-core_ruflo__neural_train({ modelType: "moe", epochs: 10 }) (modelType is required; there is no patternType)

Key sourcing & key rotation (ADR-103)

  • The witness key is a 32-byte Ed25519 private key, stored as { "privateKey": "<64-hex-chars>" } in a JSON file referenced by RUFLO_WITNESS_KEY_PATH. Keep it OUT of the repo. For local development, generate one once with node -e "import('@noble/ed25519').then(async ed=>{const sk=crypto.getRandomValues(new Uint8Array(32));console.log(Buffer.from(sk).toString('hex'))})" and write it to ~/.ruflo/witness-key.json.
  • Production deployments pin the corresponding PUBLIC key in project config and supply it as trustedPublicKey to verifyBacktestArtifact(...) — never trust the witnessPublicKey field on the artifact itself (CWE-347 / #1922).
  • Key rotation: re-sign existing backtest entries with the new key OR explicitly mark pre-rotation artifacts as non-promotable. Same pattern as ADR-103.

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