Check a dataset before analysis
Find missing values, inconsistent formats, duplicates, and questions that could invalidate results.
Build robust, production-grade backtesting systems that avoid common pitfalls and produce reliable strategy performance estimates.
--- name: backtesting-frameworks-9a66dcc81477 description: "Build robust, production-grade backtesting systems that avoid common pitfalls and produce reliable strategy performance estimates." risk: safe source: community date_added: "2026-02-27" --- # Backtesting Frameworks Build robust, production-grade backtesting systems that avoid common pitfalls and produce reliable strategy performance estimates. ## Use this skill when - Developing trading strategy backtests - Building backtesting infrastructure - Validating strategy performance and robustness - Avoiding common backtesting biases - Implementing walk-forward analysis ## Do not use this skill when - You need live trading execution or investment advice - Historical data quality is unknown or incomplete - The task is only a quick performance summary ## Instructions - Define hypothesis, universe, timeframe, and evaluation criteria. - Build point-in-time data pipelines and realistic cost models. - Implement event-driven simulation and execution logic. - Use train/validation/test splits and walk-forward testing. - If detailed examples are required, open `resources/implementation-playbook.md`. ## Safety - Do not present backtests as guarantees of future performance. - Avoid providing financial or investment advice. ## Resources - `resources/implementation-playbook.md` for detailed patterns and examples. --- <!-- AGI-INTEGRATION-START --> ## AGI Framework Integration > **Adapted for [@techwavedev/agi-agent-kit](https://www.npmjs.com/package/@techwavedev/agi-agent-kit)** > Original source: [antigravity-awesome-skills](https://github.com/sickn33/antigravity-awesome-skills) ### Memory-First Protocol Retrieve prior test strategies, known flaky tests, and coverage gaps. Cache test infrastructure setup to avoid re-configuring test environments. ```bash # Check for prior testing/QA context before starting python3 execution/memory_manager.py auto --query "test patterns and coverage strategies for Backtesting Frameworks" ``` ### Storing Results After completing work, store testing/QA decisions for future sessions: ```bash python3 execution/memory_manager.py store \ --content "Testing strategy: integration tests hit real DB (no mocks), 85% line coverage, mutation testing on critical paths" \ --type technical --project <project> \ --tags backtesting-frameworks testing ``` ### Multi-Agent Collaboration Share test results and coverage reports with code review agents so they can verify adequate coverage on changed code. ```bash python3 execution/cross_agent_context.py store \ --agent "<your-agent>" \ --action "QA complete — test suite expanded with 12 new integration tests, all passing" \ --project <project> ``` ### TDD Enforcement This skill integrates with the framework's iron-law RED-GREEN-REFACTOR cycle. No production code without a failing test first. ### Agent Team: QA Dispatch `qa_team` to generate tests and verify they pass before marking implementation complete. <!-- AGI-INTEGRATION-END -->--- name: backtesting-frameworks-9a66dcc81477 description: "Build robust, production-grade backtesting systems that avoid common pitfalls and produce reliable strategy performance estimates." risk: safe source: community date_added: "2026-02-27" --- # Backtesting Frameworks Build robust, production-grade backtesting systems that avoid common pitfalls and produce reliable strategy performance estimates. ## Use this skill when - Developing trading strategy backtests - Building backtesting infrastructure - Validating strategy performance and robustness - Avoiding common backtesting biases - Implementing walk-forward analysis ## Do not use this skill when - You need live trading execution or investment advice - Historical data quality is unknown or incomplete - The task is only a quick performance summary ## Instructions - Define hypothesis, universe, timeframe, and evaluation criteria. - Build point-in-time data pipelines and realistic cost models. - Implement event-driven simulation and execution logic. - Use train/validation/test splits and walk-forward testing. - If detailed examples are required, open `resources/implementation-playbook.md`. ## Safety - Do not present backtests as guarantees of future performance. - Avoid providing financial or investment advice. ## Resources - `resources/implementation-playbook.md` for detailed patterns and examples. --- <!-- AGI-INTEGRATION-START --> ## AGI Framework Integration > **Adapted for [@techwavedev/agi-agent-kit](https://www.npmjs.com/package/@techwavedev/agi-agent-kit)** > Original source: [antigravity-awesome-skills](https://github.com/sickn33/antigravity-awesome-skills) ### Memory-First Protocol Retrieve prior test strategies, known flaky tests, and coverage gaps. Cache test infrastructure setup to avoid re-configuring test environments. ```bash # Check for prior testing/QA context before starting python3 execution/memory_manager.py auto --query "test patterns and coverage strategies for Backtesting Frameworks" ``` ### Storing Results After completing work, store testing/QA decisions for future sessions: ```bash python3 execution/memory_manager.py store \ --content "Testing strategy: integration tests hit real DB (no mocks), 85% line coverage, mutation testing on critical paths" \ --type technical --project <project> \ --tags backtesting-frameworks testing ``` ### Multi-Agent Collaboration Share test results and coverage reports with code review agents so they can verify adequate coverage on changed code. ```bash python3 execution/cross_agent_context.py store \ --agent "<your-agent>" \ --action "QA complete — test suite expanded with 12 new integration tests, all passing" \ --project <project> ``` ### TDD Enforcement This skill integrates with the framework's iron-law RED-GREEN-REFACTOR cycle. No production code without a failing test first. ### Agent Team: QA Dispatch `qa_team` to generate tests and verify they pass before marking implementation complete. <!-- AGI-INTEGRATION-END -->
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.