Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
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Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
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Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single age
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Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single age
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Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows
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Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows
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Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows
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Initialize a multi-agent swarm with anti-drift configuration. Use when starting a complex multi-file task that needs 3+ coordinated agents (feature implementati
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Multi-agent swarm coordination for complex tasks. Use when: 3+ files need changes, new features, refactoring. Skip when: single file edits, simple fixes, docume
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Multi-agent swarm coordination for complex tasks. Uses hierarchical topology with specialized agents to break down and execute complex work across multiple file
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Test-Driven Repair — given a failing test, spawn a bounded headless `claude -p` (Read/Edit/Bash only) that makes the test pass without modifying it. Modeled on
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TDD London School workflow -- mock-first, outside-in test development
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Detect missing test coverage and generate test suggestions. Use when the user asks about coverage gaps, untested code, or what tests to write next; also after a
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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 tampe
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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 loca
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Regulator-grade feature attribution for any LSTM/Transformer signal — single-entry PageRank ranks the top-K features that drove the prediction (ADR-126 Phase 6,
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Optimize portfolio allocation using npx neural-trader mean-variance engine with risk constraints and rebalancing plan
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Mean-variance portfolio optimization via Conjugate Gradient — 40-60× faster than the legacy Neumann path (ADR-126 Phase 3, ADR-123 Wedge 8)
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Detect current market regime using npx neural-trader — bull/bear/ranging/volatile classification with recommended strategy. Use when the user asks about market
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Assess portfolio risk using npx neural-trader — VaR, CVaR, Sharpe, position sizing, circuit breaker status
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Generate trading signals using npx neural-trader anomaly detection engine with Z-score scoring and neural prediction
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Train neural models (LSTM, Transformer, N-BEATS) on market data using npx neural-trader with confidence intervals
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CLI modernization and hooks system enhancement for claude-flow v3. Implements interactive prompts, command decomposition, enhanced hooks integration, and intell
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CLI modernization and hooks system enhancement for claude-flow v3. Implements interactive prompts, command decomposition, enhanced hooks integration, and intell
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