性能
性能分析与优化
performance-optimization
addyosmani
Optimizes application performance across frontend, backend, queries, and databases. Use when performance requirements exist, when you suspect performance regressions, when Core Web Vitals or load times need improvement, when N+1 query patterns need fixing, or when profiling reveals bottlenecks.
peft-fine-tuning
majiayu000
Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.
bm-decide
basicmachines-co
Capture a durable engineering decision in Basic Memory with rationale, alternatives, consequences, and affected work. Use when the user makes or asks to record a real choice — "let's go with X", "record this decision", or runs /basic-memory:bm-decide.
bm-status
basicmachines-co
Show the Basic Memory plugin's current state for this project — active project, capture folders, output style, recent session checkpoints, and whether Basic Memory is reachable.
bm-remember
basicmachines-co
Quickly save a small fact, reminder, or user preference into Basic Memory from Codex without turning it into a full decision or checkpoint.
optimize
pbakaus
Improve interface performance across loading speed, rendering, animations, images, and bundle size. Makes experiences faster and smoother.
get-available-resources
K-Dense-AI
This skill should be used at the start of any computationally intensive scientific task to detect and report available system resources (CPU cores, GPUs, memory, disk space). It creates a JSON file with resource information and strategic recommendations that inform computational approach decisions such as whether to use parallel processing (joblib, multiprocessing), out-of-core computing (Dask, Zarr), GPU acceleration (PyTorch, JAX), or memory-efficient strategies. Use this skill before running analyses, training models, processing large datasets, or any task where resource constraints matter.
cirq
K-Dense-AI
Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.
cobrapy
K-Dense-AI
Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.
dask
K-Dense-AI
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
agent-memory-mcp
benjaminasterA
"A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions)."
threejs-materials
CloudAI-X
Three.js materials - PBR, basic, phong, shader materials, material properties. Use when styling meshes, working with textures, creating custom shaders, or optimizing material performance.
threejs-postprocessing
CloudAI-X
Three.js post-processing - EffectComposer, bloom, DOF, screen effects. Use when adding visual effects, color grading, blur, glow, or creating custom screen-space shaders.
threejs-lighting
CloudAI-X
Three.js lighting - light types, shadows, environment lighting. Use when adding lights, configuring shadows, setting up IBL, or optimizing lighting performance.
threejs-geometry
CloudAI-X
Three.js geometry creation - built-in shapes, BufferGeometry, custom geometry, instancing. Use when creating 3D shapes, working with vertices, building custom meshes, or optimizing with instanced rendering.
threejs-interaction
CloudAI-X
Three.js interaction - raycasting, controls, mouse/touch input, object selection. Use when handling user input, implementing click detection, adding camera controls, or creating interactive 3D experiences.
llm-cost-optimizer
vellum-ai
"Analyze and reduce LLM spend: read usage breakdowns by call site, model, and inference profile, understand single-winner profile resolution, and pin call sites to managed profiles (Balanced / Quality / Budget / Fast) only where they should deviate from shipped defaults."
vellum-heartbeat
vellum-ai
Configure periodic background checklist runs
bird
CoWork-OS
X/Twitter CLI for reading, searching, posting, and engagement via cookies.
add-pallas-kernel
marin-community
Add or change a named Pallas/Mosaic kernel, including its reference implementation, correctness tests, wrapper, or requested tuning.
ab-test-zephyr
marin-community
Run an explicitly requested Zephyr control/treatment benchmark on the same pre-normalized sample and compare Finelog stage metrics.
sno-mem-codex
sno-ai
Use Sno memory from Codex through four explicit commands.
judge-retired-position
sno-ai
Judge whether one stored row states a retired profile position as current.
judge-rem-memory-updates
sno-ai
Judge REM memory relations, rewrites, verification, and clause carry by meaning. Use for REM update model calls that decide which older facts are superseded, which facts remain current, and whether a proposed rewrite preserves all surviving facts.