framework-internals
1.7K
simple-math
Perform basic arithmetic operations safely using standard operators without eval or exec
cisco-ai-defense
development
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framework-internals
1.6K
neo4j-cypher-guide
Comprehensive guide for writing modern Neo4j Cypher read queries. Essential for text2cypher MCP tools and LLMs generating Cypher queries. Covers removed/deprecated syntax, modern replacements, CALL subqueries for reads, COLLECT patterns, sorting best practices, and Quantified Path Patterns (QPP) for efficient graph traversal.
tomasonjo
development
framework-internals
1.5K
quartz-integration
Integration guide for using the Quartz Nostr KMP library in external projects. Use when: (1) adding Quartz as a Gradle dependency, (2) setting up NostrClient with WebSocket, (3) creating/signing/sending events, (4) building relay subscriptions with Filter, (5) handling keys with KeyPair/NostrSignerInternal, (6) using Bech32 encoding/decoding (NIP-19), (7) platform-specific setup (Android vs JVM/Desktop), (8) NIP-57 zaps, NIP-17 DMs, NIP-44 encryption in external projects.
vitorpamplona
development
framework-internals
1.5K
impl-jit-kernel
Guide for implementing CUDA or CPU JIT kernels in mllm-kernel. Use when the user asks to create, add, or implement a new kernel in mllm-kernel.
UbiquitousLearning
development
framework-internals
1.3K
pennylane
Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms (VQE, QAOA), quantum neural networks, and integration with PyTorch/JAX/TensorFlow. For hardware-specific optimizations use qiskit (IBM) or cirq (Google); for open quantum systems use qutip.
foryourhealth111-pixel
development
framework-internals
1.3K
noir-optimize-acir
Workflow for measuring and optimizing the ACIR circuit size of a constrained Noir program. Use when asked to optimize a Noir program's gate count or circuit size.
noir-lang
development
framework-internals
1.3K
better-result-adopt
Adopt better-result in an existing TypeScript codebase. Use when replacing try/catch, Promise rejection handling, null sentinels, or thrown domain exceptions with typed Result workflows.
dmmulroy
development
framework-internals
1.3K
atmos-toolchain
Toolchain management: install/exec/search/env commands, Aqua registry integration, version pinning, multi-tooling execution
cloudposse
development
framework-internals
1.2K
fix-provider
Fix Provider, Collector, Transformer compilation errors
wrtnlabs
development
framework-internals
1.2K
implement-spec
Implement a specification (or specific phases of a spec) using coordinated subagents. Handles multi-phase spec implementation with unit tests, integration tests, documentation, and code-review compliance. Use when the user says "implement spec", "implement the spec", "implement a dated spec file", "implement phases", "build from spec", or "code the spec". Tracks progress by updating the spec with implementation status.
open-mercato
development
framework-internals
1.2K
system-extension
Extend core modules using the Universal Module Extension System (UMES). Use when adding columns/fields/filters to existing tables/forms, enriching API responses, intercepting API routes, blocking/validating mutations, replacing UI components, injecting menu items, or reacting to domain events. Triggers on "extend", "add column to", "add field to", "inject into", "intercept", "enrich", "hook into", "customize", "override component", "add menu item", "react to event", "block mutation", "validate before save".
open-mercato
development
framework-internals
1.2K
llama-cpp
Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.
math-inc
development
framework-internals
1.2K
tensorrt-llm
Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.
math-inc
development
framework-internals
1.2K
huggingface-accelerate
Simplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. Automatic device placement, mixed precision (FP16/BF16/FP8). Interactive config, single launch command. HuggingFace ecosystem standard.
math-inc
development
framework-internals
1.2K
optimizing-attention-flash
Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers with long sequences (>512 tokens), encountering GPU memory issues with attention, or need faster inference. Supports PyTorch native SDPA, flash-attn library, H100 FP8, and sliding window attention.
math-inc
development
framework-internals
1.2K
pytorch-lightning
High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.
math-inc
development
framework-internals
1.2K
distributed-llm-pretraining-torchtitan
Provides PyTorch-native distributed LLM pretraining using torchtitan with 4D parallelism (FSDP2, TP, PP, CP). Use when pretraining Llama 3.1, DeepSeek V3, or custom models at scale from 8 to 512+ GPUs with Float8, torch.compile, and distributed checkpointing.
math-inc
development
framework-internals
1.1K
add-compiler-option
Adds a new compiler option to Metro.
ZacSweers
development
framework-internals
1.1K
cute-dsl-kernel
Use when writing, modifying, porting, or optimizing CuTe DSL GPU kernels in Python; reading CuTe DSL API reference material; integrating a CuTe DSL kernel into a project; or rewriting an existing CUDA or C++ operator into CuTe DSL while preserving correctness and performance expectations.
vipshop
development
framework-internals
1.1K
operator-migration
Use when doing operator migration or kernel migration for CUDA, Triton, or custom ops in cache-dit; porting kernels from nunchaku, deepcompressor, or other repos; designing operator registration and public wrappers; wiring build and packaging for optional extensions; or reviewing an operator migration plan. Guides survey, minimal-closure migration, API design, extension loading, packaging, and layered validation. Do not use for blind copy-paste ports.
vipshop
development
framework-internals
1.1K
golang-naming
Go (Golang) naming conventions — covers packages, constructors, structs, interfaces, constants, enums, errors, booleans, receivers, getters/setters, functional options, acronyms, test functions, and subtest names. Use this skill when writing new Go code, reviewing or refactoring, choosing between naming alternatives (New vs NewTypeName, isConnected vs connected, ErrNotFound vs NotFoundError, StatusReady vs StatusUnknown at iota 0), debating Go package names (utils/helpers anti-patterns), or asking about Go naming best practices. Also trigger when the user mentions MixedCaps vs snake_case, ALL_CAPS constants, Get-prefix on getters, or error string casing. Do NOT use for general Go implementation questions that don't involve naming decisions.
samber
development