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AI Code Review with Full Control Over Model Choice and Costs.
72 tagged coding assistant, measured the same way as everything else here.
Browse within: best-practices 26clean-code 26educational-project 23cursor-ide 12ai-integration 10
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AI Code Review with Full Control Over Model Choice and Costs.
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Devenv Container and Docker Integration.
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Rust CLI Best Practices with clap.
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Rust Observability and Logging Best Practices.
itxaiohanglover/mcp-codestyle-server
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A rule for analyzing or changing code through the project’s codestyle tools. It requires starting with a project analysis or code-context exploration before reading or editing individual code areas.
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General project rules that applies to all file types. Should be most general.
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Applies general TypeScript best practices and style guidelines to all TypeScript files in the project.
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You are building an AI/ML project with Python. The project uses PyTorch for model training, handles data pipelines with proper validation, tracks experiments systematically, and follows production ML engineering practices. Code is type-hinted, tested, and reproducible.
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AI/ML Python development (PyTorch, scikit-learn).
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When developing MCP DevTools packages, prefer using shared core libraries over custom implementations to ensure consistency and maintainability.
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Guidelines for Creating a New MCP Server Package.
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The MCP DevTools repository follows a monorepo structure with clear organization of packages and shared resources.
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Replen integration — session-start matches, portfolio recall, silent auto-reground.
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Unloop: AI fix loop detection, prevention, and recovery system. Monitors every error fix attempt using fingerprinting and similarity analysis. Provides escalating intervention (NUDGE → WARNING → CRITICAL) with context-aware escape strategies. MANDATORY protocol for all error-fixing activity.
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Interactive Loop + Professional Consultant Mode.
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Subtraction-first engineering — smallest correct change wins.
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Read .apc/manifest.md first. If it contains placeholders and the user requests initialization, follow .apc/init.md. If the task concerns APC itself, edit prompt source without filling consumer placeholders. Otherwise follow .apc/workflow.md §0 or §1.
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Before the final summary, follow .apc/workflow.md §4. Persist only material, verified knowledge or state; no-op is valid.
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ContextOS core project rules and role orchestration.
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Systematic 6-phase engineering pipeline (DEFINE → PLAN → BUILD → VERIFY → REVIEW → SHIP) enforcing role declarations, atomic task execution, quality gates, and regression prevention.
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A brief summary of what the skill does and its core philosophy.
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You have the AI Mind Map MCP server connected. It is a persistent code memory system that eliminates redundant file re-reading and context loss between sessions.