ML Ops
Machine learning operations
xiaoyuzhou-podcast-transcriber
by nanzhipro
"Downloads Xiaoyuzhou podcasts, transcribes using FunASR, and generates raw, structured, and optimized text files. Invoke when user provides a Xiaoyuzhou episode link."
angular-component-inputs
by araujomartin
Modern function-based component inputs and models using Angular Signals API. Trigger: When defining component inputs, when migrating from decorators, when working with reactive component APIs, when implementing two-way binding.
DreamerV3-Style RSSM World Model
by sovr610
This skill should be used when the user asks to "implement DreamerV3 RSSM", "build a recurrent state space model", "create Block GRU sequence model", "implement unimix categorical", "add symlog twohot prediction heads", "implement KL balancing loss", "free nats clipping", "world model loss function", "imagination rollout for actor-critic", "straight-through categorical estimator", "implement prior and posterior networks", "DreamerV3 world model", "symlog transform", "twohot encoding 255 bins", "prevent codebook collapse", "DreamerV3 numerical stability", "scale-invariant reward prediction", "world model imagination", "RSSM prior posterior KL divergence", "Block GRU with RMSNorm", "categorical latent state 32x32", or needs guidance on implementing DreamerV3-style world models with the full set of numerical stability techniques (symlog, twohot, unimix, KL balancing).
circleci-config-generator
by ehtbanton
Generate CircleCI configuration files with workflows, orbs, and deployment. Triggers on "create circleci config", "generate circleci configuration", "circleci pipeline", "circle ci setup".
V-JEPA 2 Data Pipeline
by sovr610
This skill should be used when the user asks to "load video dataset", "implement video transforms", "data augmentation for V-JEPA", "video decoding with decord", "clip sampling", "frame padding", "RandAugment for video", "motion shift augmentation", "random erasing", "video normalization", "YAML config parsing", "dataset registry", "distributed sampler", "weighted sampling", "multi-source dataset", "video DataLoader", "worker seeding", or needs guidance on video data loading, augmentation pipelines, configuration management, or dataset engineering for V-JEPA 2.
tinker-api
by dinequickly
Guide for using the Tinker API for LLM training. Use when working with Tinker training workflows, RL environments, supervised fine-tuning, model sampling, rendering, or any Tinker API operations.
sqlalchemy
by Nomik94
SQLAlchemy 2.0 async infrastructure pattern reference. Use when: DB model definition, Base model setup, table mapping, relationship config, session management, AsyncSession, sessionmaker, connection pool, query patterns (select, join, subquery, pagination), Mixin (Timestamp, SoftDelete), N+1 prevention (selectinload, joinedload), transaction management, nested transaction, savepoint, generic repository pattern, BaseRepository[ModelType]. NOT for: domain entity design (domain-layer skill), Alembic migrations.
peer-review
by pietz
Ask a group of LLM tools for their opinion on a given task. Use this when stuck on a problem, seeking a second opinion, validating an approach, or wanting diverse viewpoints on complex decisions.
Global Workspace Competition + Broadcast + Working Memory with Ignition Dynamics
by sovr610
This skill should be used when the user asks to "implement global workspace", "add workspace competition", "implement ignition dynamics", "add broadcast adapters", "implement working memory", "add CfC/LTC memory", "implement attention competition", "add token staging", "implement slot construction", "add deterministic tie-breaking", "implement iterative rounds", "add convergence detection", "implement ignition gate", "add lock-in prevention", "implement broadcast to temporal", "add broadcast to symbolic", "implement broadcast to decision", "add workspace slots", "implement capacity-limited selection", "add novelty scoring", "implement winner decay", "add slot dropout", "implement ignition cooldown", "add feedback collection", "implement workspace state persistence", "add truncated BPTT support", "implement GRU fallback for workspace", "add workspace telemetry", or mentions global neuronal workspace theory, multi-modal token competition, ignition threshold dynamics, workspace broadcast packets, or CfC/LTC working memory in the cognitive pipeline.
live-workshop
by janineagu4049
Set up a JupyterBook-based workshop journal with live audio transcription, keyword extraction, and structured knowledge base. Use when attending lectures, workshops, or meetings that need real-time note-taking and organized output.
movie-maker
by LongStories
Docs-first AgentSkill for generating 10-60s mini-movies locally. Provides rules for scripts, shotlists, timing, prompting, providers, rendering (ffmpeg/remotion), and sharing to clawtube.
Auto Orchestrator Skill
by smouj
OpenClaw skill: auto-orchestrator
cohere-rerank
by RSHVR
Cohere reranking reference for two-stage retrieval, semantic search improvement, and RAG pipelines. Covers Rerank v4 models, structured data reranking, and LangChain integration.
pipeline-pattern-python
by progmichaelkibenko
Implements the Pipeline design pattern in Python for data transformation. Use when the user mentions pipeline pattern, or when you need a fixed sequence of stages that each transform data and pass to the next—ETL, parsing, data processing, or any linear transformation flow that runs to completion.
ai-vision-go
by httprunner
Multimodal UI understanding and single-step planning via OpenAI-compatible Responses APIs. Use when you need AIQuery/AIAssert and plan-next to extract UI element coordinates, validate UI assertions, summarize screenshots, or decide the next UI action from an image. External agents handle execution via adb/hdc and multi-step loops. Defaults to Doubao models but can be pointed at other multimodal providers via base URL, API key, and model name.
pack
by pmco23
Pack the local codebase using Repomix CLI into three targeted snapshots (code, docs, full) stored in .pipeline/ for sharing across /qa audit agents. Run before /qa for maximum token efficiency. Usage: /pack [path] (defaults to cwd).
hermes-multi-agent-orchestrator
by L-MORIA
Multi-agent orchestration for Hermes Agent using OpenCode Zen free models. 5 proven patterns: Council (parallel), Pipeline (sequential), Hybrid. Roles: Architect (Big Pickle Med), Planner/Researcher (Deepseek V4 Flash), Coder (North Mini Code), Synthesizer (Mimo V2.5), Reviewer (Nemotron 3 Ultra).
langfuse-observation-view
by neuradex
View Langfuse observation (Generation/Span) details. Use when checking specific LLM call input/output, debugging issues, or analyzing costs.
Affective State Estimator (Valence-Arousal + Appraisal + Modulation)
by sovr610
This skill should be used when the user asks to "add emotion layer", "affective state estimation", "valence-arousal model", "emotional modulation of learning", "appraisal theory computation", "mood-congruent processing", "amygdala-inspired module", "somatic marker", "intrinsic motivation signal", "curiosity-driven exploration", "frustration detection", "reward prediction affect", "homeostatic regulation", "implement affective modulator", "add valence arousal space", "implement appraisal module", "add emotional bias to decisions", "implement somatic marker hypothesis", "add intrinsic reward signal", "implement dimensional emotion model", "add affect-modulated learning rate", "implement curiosity-anxiety tradeoff", "add frustration-driven exploration", or mentions affective state, valence-arousal, appraisal theory, emotional modulation, somatic markers, intrinsic motivation, mood-congruent processing, or homeostatic regulation in the cognitive pipeline.
sbv2-tts
by route250
Style-Bert-VITS2 音声生成を行う。uvxが必要
pipeline-pattern-go
by progmichaelkibenko
Implements the Pipeline design pattern in Go for data transformation. Use when the user mentions pipeline pattern, or when you need a fixed sequence of stages that each transform data and pass to the next—ETL, parsing, data processing, or any linear transformation flow that runs to completion.
mistral-packaging-compat-check
by Haruk1y
Validate compatibility between Mistral model packaging format and inference path, including adapter versus merged full-model loading. Use when merged models fail generation or runtime/tokenizer artifacts are inconsistent.
paper-builder
by kawah-ren
Guide users to build rigorous academic papers step-by-step in standard LaTeX format, with strict blocking for asset requests. Also generates modular, runnable PyTorch code for EEG/BCI experiments (dataset loading, model architecture, LOSO training loop) when the user needs to run experiments before writing. Use this skill whenever the user wants to write an academic paper, prepare a manuscript, create a LaTeX document, or needs PyTorch experiment code for EEG decoding, BCI, motor imagery, or related computational neuroscience tasks. Trigger when the user mentions writing a paper, running experiments, training a model, LOSO cross-validation, preparing a manuscript, or formatting research for IEEE/ACM/Nature venues.
mistral-hidden-params-ft
by Haruk1y
Run end-to-end fine-tuning for request_text-to-hidden-params JSON prediction with Ministral-3-3B in this repository. Use when rebuilding train/validation/test splits from train-only data, converting data to prompt-completion format, launching TRL SFT on Hugging Face Jobs, validating strict JSON output behavior, merging LoRA adapters into full models, and reporting job/model status with links.