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Shareable instruction files for Cursor, Claude Code, Copilot, Windsurf, and more — installed alongside your existing agent rules.
This file provides persistent instructions for AI coding agents (Cursor, Copilot, Codex, etc.) working on this codebase. Human contributors should also refer to [CONTRIBUTING.md](CONTRIBUTING.md).
**Table of Contents** For a broad overview of reinforcement learning, imitation learning and all the training scenarios, methods and options within the ML-Agents Toolkit, see [ML-Agents Toolkit Overview](ML-Agents-Overview.md).
> Create and use specialized AI subagents in Claude Code for task-specific workflows and improved context management. Subagents are specialized AI assistants that handle specific types of tasks. Each subagent runs in its own context window with a custom system prompt, specific tool access, and independent permissions. When Claude encounters a task that matches a subagent's description, it delegates to that subagent, which works independently and returns results. To see the context savings in pra
LLMs excel at **synthesis and critique** when given **bounded, well-structured inputs**. This module wraps provider calls into **role-specific agents** (analysts, researchers, trader, risk) that all speak the same **state dictionary** contract expected by `DecisionExecutor` and `workflow.build_analyst_chain`. Without this layer, prompt strings would be scattered across routes and scripts—untestable and unsafe to evolve.
"""Short description of the function or class. Detailed description using reStructuredText format. Description of param1 Description of param2 Description of return value >>> obj = ExampleClass() <git_commit_standards>
This is the universal AI skills library — 204 production-ready skill packages across 13 professional domains with 559 Python automation tools and 12 sample CI/CD workflows. It works with every major AI coding assistant.
fn test_module_functionality() { ExtBuilder::default().build().execute_with(|| { <module_documentation> <item>Clear overview of module purpose</item> <item>Detailed interface documentation</item> <item>Usage examples</item>
**For any information about the codebase (structure, logic, or usage), you MUST use RagCode MCP tools.** Never guess code details from memory; always search the local index first using `search_code` or `get_function_details`.
> **You are Cascade, the AI inside Windsurf IDE by Codeium.** > **Model**: Claude Sonnet 4.6 / Codeium model (varies) > **Aura Version**: v0.7.1 > **Integration**: Terminal commands