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229 lines
10 KiB
Markdown
229 lines
10 KiB
Markdown
# AGENTS.md - QuanTAlib Protocol
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> **To all AI Agents:** This file defines the laws, physics, and protocols of the QuanTAlib repository. Read this before writing a single line of code. Failure to adhere to these standards will result in rejected code.
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## 1. Identity & Mission
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**QuanTAlib** is a high-performance, zero-allocation C# library for quantitative technical analysis.
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* **Target**: Quantower and custom C# trading engines.
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* **Core Philosophy**: Speed, Correctness, and Memory Efficiency.
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* **Key Constraint**: Hot paths must be allocation-free (GC pressure is the enemy).
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## 2. Architecture & "Physics"
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### Memory Model: Structure of Arrays (SoA)
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We do not store objects in lists. We store primitive arrays.
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* **TSeries**: Internally uses `List<long> _t` (timestamps) and `List<double> _v` (values).
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* **Access**: Expose data via `ReadOnlySpan<double>` for SIMD operations.
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### Core Types
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* `TValue`: Struct (16 bytes). `DateTime Time`, `double Value`.
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* `TBar`: Struct (48 bytes). `DateTime Time`, `double Open, High, Low, Close, Volume`.
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* `TSeries`: The primary data structure for time series.
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* `ITValuePublisher`: The interface for reactive data flow.
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### Design Principles
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* **Source Material:** The algorithm and markdown documentation foundation should be sourced from [https://github.com/mihakralj/pinescript/blob/main/indicators/](PineScript).
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* **Zero Allocation:** The core calculation loop must not allocate memory on the heap. Use `stackalloc`, `Span<T>`, and pinned memory where possible.
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* **O(1) Complexity:** Streaming updates must be O(1) whenever mathematically possible. Use running sums/products or circular buffers to avoid re-iterating over history.
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* **Dual API:** Provide both a stateful object-oriented API (`Update`) and a stateless static vector API (`Calculate`).
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* **Bar Correction:** Support intra-bar updates via the `isNew` parameter. The indicator must be able to rollback the last update and apply a new value for the same timestamp.
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* **Robustness:** Handle `NaN` and `Infinity` gracefully using last-valid-value substitution. Never propagate invalid values.
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* **Reactive:** Implement `ITValuePublisher` to support event-driven architectures.
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* **Time Handling:** Always use `DateTime.UtcNow` instead of `DateTime.Now` to ensure consistent time handling across timezones.
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### Performance Rules
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1. **Zero Allocation**: The `Update` method MUST NOT allocate memory on the heap. Use `stackalloc` or pre-allocated buffers.
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2. **O(1) Complexity**: Streaming updates must be constant time. Use circular buffers (`RingBuffer`) or running sums.
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3. **SIMD**: Batch operations (`Calculate`) should use `System.Runtime.Intrinsics` (AVX2) where possible. If SIMD is not possible due to recursive dependencies, use `stackalloc` for internal buffers to avoid heap allocations.
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4. **Inlining**: Use `[MethodImpl(MethodImplOptions.AggressiveInlining)]` on hot methods.
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5. **Locals**: Use `[SkipLocalsInit]` to avoid zero-init costs in tight loops.
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## 3. Indicator Implementation Standards
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Every indicator must follow the **Good Indicator Guidelines** strictly.
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### File Structure
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Directory: `lib/[category]/[name]/` (e.g., `lib/trends/sma/`)
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| File | Naming | Purpose |
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|------|--------|---------|
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| **Source** | `[Name].cs` | Main implementation. `public sealed class`. |
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| **Tests** | `[Name].Tests.cs` | xUnit tests (correctness, edge cases). |
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| **Validation** | `[Name].Validation.Tests.cs` | Compare against TA-Lib, Skender, etc. |
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| **Docs** | `[Name].md` | User documentation with formulas. |
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| **Adapter** | `[Name].Quantower.cs` | Quantower platform integration. |
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| **Adapter Tests** | `[Name].Quantower.Tests.cs` | Tests for the adapter. |
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### Class Definition
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* **Namespace:** `QuanTAlib`
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* **Attributes:** `[SkipLocalsInit]` for performance.
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* **Modifiers:** `public sealed class`
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* **Interface:** Implements `ITValuePublisher`
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### State Management
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* **Scalar State:** Use a `private record struct State` to group all scalar state variables. This ensures value semantics, automatic `IEquatable` implementation, and cleaner rollback logic.
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* **State Variables:** Maintain `private State _state;` (current) and `private State _p_state;` (previous valid state).
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* **Buffers:** Use `RingBuffer` for sliding window data.
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* **Resync:** Implement a periodic full recalculation (e.g., every 1000 ticks) to prevent floating-point drift in running sums.
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### Constructor
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* Validate all parameters (throw `ArgumentException` for invalid values).
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* Initialize `Name` property (e.g., `$"Sma({period})"`);
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* Support chaining: `public [Name](ITValuePublisher source, ...)`
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### The `Update` Method Contract
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The `Update` method is the heart of the indicator.
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```csharp
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public TValue Update(TValue input, bool isNew = true)
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```
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* **Attribute:** `[MethodImpl(MethodImplOptions.AggressiveInlining)]`
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* **Logic:**
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1. **State Rollback:**
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```csharp
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if (isNew) {
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_p_state = _state;
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// ... update state (e.g. counters) ...
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} else {
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_state = _p_state;
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// ... update state ...
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}
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```
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2. **Input Validation:** Check `double.IsFinite`. If not, use `_lastValidValue` (stored in `State`).
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3. **Calculation:** Perform the math.
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4. **Publish:** Update `Last` property, invoke `Pub` event, return `Last`.
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### Update Method (TSeries)
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* **Signature:** `public TSeries Update(TSeries source)`
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* **Placement:** Must be adjacent to the `Update(TValue)` method.
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* **Logic:**
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1. Create output series.
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2. Call static `Calculate(Span)` for performance.
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3. Restore internal state by replaying the last `Period` bars (or full series if recursive).
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### Static Calculate (TSeries)
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* Create a new instance of the indicator.
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* Iterate through the source series.
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* Return the resulting `TSeries`.
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### Static Calculate (Span) - **Critical for Performance**
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* **Signature:** `public static void Calculate(ReadOnlySpan<double> source, Span<double> output, ...)`
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* **Attribute:** `[MethodImpl(MethodImplOptions.AggressiveInlining)]`
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* **Optimization:**
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* Check for SIMD support (`Avx2.IsSupported`).
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* Use `stackalloc` for small buffers (threshold ~256) and for internal state buffers in recursive algorithms where SIMD is not applicable.
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* Implement a scalar fallback path that handles `NaN` safely.
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* Implement a SIMD path for large, clean datasets (optional but recommended for simple averages).
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## 4. Testing Protocol
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### Unit Tests (`[Name].Tests.cs`)
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* **Framework:** xUnit
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* **Data Generation:** Use `GBM` (Geometric Brownian Motion) for generating realistic test data. Avoid using `System.Random` directly.
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* **Coverage:**
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* Constructor validation (invalid params).
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* Basic calculation correctness (compare against manual calc).
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* `isNew=true` vs `isNew=false` behavior (bar correction).
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* `Reset()` functionality.
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* `IsHot` property behavior.
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* `NaN` / `Infinity` handling (must not crash, must return finite values).
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* Consistency between Object API, Static TSeries API, and Static Span API.
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* Edge cases: Period=1, empty input, single input.
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### Validation Tests (`[Name].Validation.Tests.cs`)
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* **Mandatory**: You MUST validate against at least one external authority (TA-Lib, Skender, Tulip, OoplesFinance, Python libs).
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* **Tolerance**: Typically `1e-6` to `1e-9`.
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* **Data**: Use `ValidationTestData` class which wraps `GBM` (Geometric Brownian Motion) to generate realistic test data and provides pre-calculated Skender quotes.
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#### External Library Usage Guide
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* **Skender.Stock.Indicators:**
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* Use `_data.SkenderQuotes.Get[Indicator](...)`.
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* Compare using `ValidationHelper.VerifyData`.
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* **TA-Lib (TALib.NETCore):**
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* Namespace: `using TALib;`
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* Method: `TALib.Functions.[Indicator]<double>(...)`.
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* Check `Assert.Equal(Core.RetCode.Success, retCode)`.
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* Use `ValidationHelper.VerifyData` with `outRange` and `lookback`.
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* **Tulip (Tulip.NETCore):**
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* Namespace: `using Tulip;`
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* Method: `Tulip.Indicators.[indicator].Run(...)`.
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* Handle lookback/offset manually (Tulip output is shorter than input).
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* Use `ValidationHelper.VerifyData` with `lookback`.
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* **OoplesFinance.StockIndicators:**
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* Namespace: `using OoplesFinance.StockIndicators;`
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* Convert data: `_data.SkenderQuotes.Select(q => new TickerData { ... }).ToList()`.
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* Use `new StockData(ooplesData).Calculate[Indicator](...)`.
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* Compare using `ValidationHelper.VerifyData`.
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## 5. Documentation Standards
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* **Format**: Markdown.
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* **Content**: Title, Description, Parameters, Formula (LaTeX), C# Usage Examples.
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* **Index**: Add the new indicator to the category index (e.g., `lib/trends/_index.md`).
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* **Linting**: Ensure that markdownlint shows no issues for the file.
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* **MD030:** Ensure exactly one space after list markers.
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* **MD032:** Ensure lists are surrounded by blank lines.
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## 6. Quantower Adapter
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* **Implementation:** Create a wrapper class in `[Name].Quantower.cs` that adapts the QuanTAlib indicator for the Quantower platform.
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* **Tests:** Create unit tests in `[Name].Quantower.Tests.cs` to verify the adapter's functionality using mocks where necessary.
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## 7. Code Review
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* **Tool:** Run CodeRabbit on the changes.
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* **Requirement:** Address and fix **ALL** issues identified by the CodeRabbit review before considering the task complete.
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## 8. Development Checklist
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When creating a new indicator, you are **DONE** only when:
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* [ ] Source algorithm is verified.
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* [ ] All 6 required files exist.
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* [ ] `Update` handles `isNew` and `NaN` correctly.
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* [ ] No heap allocations in `Update`.
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* [ ] Static `Calculate(Span)` is implemented.
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* [ ] Unit tests pass (including edge cases).
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* [ ] Validation tests pass against external libs.
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* [ ] Documentation is complete and linked in `_index.md`.
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* [ ] Quantower adapter and tests are implemented.
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* [ ] CodeRabbit review issues are resolved.
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## 9. Forbidden Actions
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* **DO NOT** use LINQ in hot paths (`Update` or `Calculate`).
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* **DO NOT** use `new` inside `Update`.
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* **DO NOT** change `Directory.Build.props` without explicit instruction.
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* **DO NOT** remove `[SkipLocalsInit]` or `[MethodImpl]` attributes.
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* **DO NOT** ignore `NaN` inputs; handle them safely.
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## 10. Context & Resources
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* **Time**: Use `DateTime.UtcNow`.
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* **Math**: Use `System.Math` or `System.Numerics`.
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* **Root Namespace**: `QuanTAlib`.
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