MLOps

ai-model-inference

Eitanvinokur12345

"Running large language models (LLMs) locally on consumer hardware."

text-to-voice

kenneropia

Convert text to speech using Kyutai's Pocket TTS. Use when the user asks to "generate speech", "text to speech", "TTS", "convert text to audio", "voice synthesis", "generate voice", "read aloud", or "create audio from text". Supports voice cloning from audio samples and multiple pre-made voices (alba, marius, javert, jean, fantine, cosette, eponine, azelma).

eve-pipelines-workflows

Incept5

Define and run Eve pipelines and workflows via manifest and CLI. Use when wiring build, release, deploy flows or invoking workflow jobs.

domain-ml

lywa1998

"Use when building ML/AI apps in Rust. Keywords: machine learning, ML, AI, tensor, model, inference, neural network, deep learning, training, prediction, ndarray, tch-rs, burn, candle, 机器学习, 人工智能, 模型推理"

web-research

engsimsoft

Глубокий поиск информации в интернете. Загрузи этот skill для сложного исследования или когда нужно проверить много источников.

pytorch-distributed

cuba6112

Distributed training strategies including DistributedDataParallel (DDP) and Fully Sharded Data Parallel (FSDP). Covers multi-node setup, checkpointing, and process management using torchrun. (ddp, fsdp, distributeddataparallel, torchrun, nccl, rank, process-group)

qwen-tts

paki81

Local text-to-speech using Qwen3-TTS-12Hz-1.7B-CustomVoice. Use when generating audio from text, creating voice messages, or when TTS is requested. Supports 10 languages including Italian, 9 premium speaker voices, and instruction-based voice control (emotion, tone, style). Alternative to cloud-based TTS services like ElevenLabs. Runs entirely offline after initial model download.

Model Export & Serving

sovr610

This skill should be used when the user asks to "export the model", "convert to ONNX", "trace with TorchScript", "quantize the model", "deploy the model", "create API server", "serve predictions", "containerize the model", "optimize for inference", "export to INT8", "create FastAPI endpoint", "set up model serving", "prune the model", "distill knowledge", "create Docker image", or needs guidance on model export formats, quantization strategies, serving infrastructure, or deployment pipelines for the brain_ai system.

quality-documentation-manager

nimeshgurung

Senior Quality Documentation Manager for comprehensive documentation control and regulatory document review. Provides document management system design, change control, configuration management, and regulatory documentation oversight. Use for document control system implementation, regulatory document review, change management, and documentation compliance verification.

everclaw

profbernardoj

Open-source first AI inference — GLM-5 as default, Claude as fallback only. Own your inference forever via the Morpheus decentralized network. Stake MOR tokens, access GLM-5, GLM-4.7 Flash, Kimi K2.5, and 30+ models with persistent inference by recycling staked MOR. Open-source first model router routes all tiers to Morpheus by default — Claude only kicks in as an escape hatch when needed. Includes Morpheus API Gateway bootstrap for zero-config startup, OpenAI-compatible proxy with auto-session management, automatic retry with fresh sessions, OpenAI-compatible error classification to prevent cooldown cascades, multi-key auth rotation v2 with proactive DIEM balance monitoring and reactive 402 watchdog, Gateway Guardian v5 with direct curl inference probes (eliminates Signal spam), proactive Venice DIEM credit monitoring, circuit breaker for stuck sub-agents, nuclear self-healing restart, always-on proxy-router with launchd auto-restart, smart session archiver, three-shift cyclic execution engine (v2 with 15-minute execution loops), 24/7 always-on power configuration for macOS, bundled security skills, zero-dependency wallet management via macOS Keychain, x402 payment client for agent-to-agent USDC payments, ERC-8004 agent registry reader for discovering trustless agents on Base, and hardware-aware local Ollama fallback with auto model selection (Qwen3.5 family, 1.5B–72B based on available RAM/GPU).

agents-management

relux-works

Spawning and managing heterogeneous agentic systems and the model vendors behind them, through the agents-management Go module and CLI. Use for agentic-system plugins (claude-code, codex, qwen-code, gemini-cli, antigravity, muse), vendor plugins (anthropic, openai, alibaba, google), runtime declarations, per-model reasoning-effort vocabularies, capability ranking, general plugin graphs, inference engines, multi-node launch plans (argv/env/stdin), provider limit state and availability verdicts. Not a task board: roles, tasks and reviews live in project-management. Russian triggers: агент, спавн, раннтайм, вендор, лимиты, модели, эффорт.

harness-wake

woahwhattheheck

Build or test a bounded Commons → harness wake loop. Use when the job is a job_id / watchdog / Cursor Slack resume / stop-without-model tick — not a new callback URL and not burying the adapter inside the MCP post pack.

mistral-model-ft-playbook

Haruk1y

Build, fine-tune, evaluate, and ship Mistral-family models with Hugging Face and PEFT, with emphasis on strict JSON outputs and model-format compatibility. Use when choosing Mistral model variants, deciding prompting vs fine-tuning, preparing {prompt, completion} or chat datasets, running SFT jobs, validating generation failures, and deciding adapter-only vs merged full-model distribution.

prompt-caching

anilsoylu

Guide for optimizing prompt caching in agentic AI applications. Use when building Claude agents, optimizing API costs, designing system prompts, managing tool definitions, implementing compaction, or troubleshooting cache miss rates. Triggers: "prompt caching", "cache hit rate", "reduce API costs", "system prompt ordering", "tool definitions caching", "compaction", "context window management", "agent cost optimization", "prefix caching", "cache-safe forking", "agentic loop cost", "token cost reduction", "cache miss debugging".

qa

pmco23

Use after /build to run the full post-build QA pipeline. Supports --parallel (all audits simultaneously) or --sequential (denoise → qf → qb → qd → security-review in order). Requires .pipeline/build.complete.

create-agent-skills

myuon

新しい Claude Code スキルを作成するためのガイド。スキルの作り方、SKILL.md の書き方、配置場所を案内する。

model-router

cgk-platform

Cost-optimized bi-directional model routing. Downgrade routine tasks to Flash, upgrade complex tasks to Opus.

eve-local-dev-loop

Incept5

Local Docker Compose development loop for Eve-compatible apps, with handoff to staging deploys.

AI Security Engineer

anorbert-cmyk

AI Security Engineer focused on preventing prompt injection, data exfiltration, and model abuse in LLM-enabled products.

SystematicNotes —— 自动化课程笔记生成系统

CoEvolution-Labs

自动化课程资料整理与笔记生成系统 — 把 PPT + 录音 → 图文并茂的精品 Markdown 笔记

OpenClinXR

simnova

Brand Name Comparison

MaxGhenis

Use this skill when the user wants to compare multiple brand name fates side-by-side to divine which is destined for success.

browser-onnx

thongnt0208

"Implements high-performance local machine learning inference in the browser using ONNX Runtime Web. Use this skill when the user needs privacy-first, low-latency, or offline AI capabilities (e.g., image classification, object detection, or NLP) without server-side processing."

Continual Learning Guard (EWC / SI / Progressive Networks / Replay)

sovr610

This skill should be used when the user asks to "prevent catastrophic forgetting", "elastic weight consolidation", "EWC regularization", "progressive networks", "continual learning strategy", "knowledge distillation for retention", "replay buffer memory", "task boundary detection", "fisher information matrix", "synaptic intelligence", "PackNet pruning", "memory-aware synapses", "add continual learning guard", "implement EWC penalty", "add experience replay", "implement progressive columns", "add Fisher diagonal computation", "implement reservoir sampling", "add knowledge distillation loss", "implement task-free continual learning", "add online EWC", "implement generative replay", "add PackNet iterative pruning", "implement synaptic intelligence path integral", or mentions catastrophic forgetting, continual learning, lifelong learning, sequential task training, knowledge retention, task interference, Fisher information regularization, or Phase 8 continual-learning pipeline in the cognitive architecture.