ML Ops
Machine learning operations
convert-elm-elixir
by aRustyDev
Convert Elm code to idiomatic Elixir. Use when migrating Elm frontend applications to Elixir (Phoenix LiveView), translating Elm's functional patterns to Elixir, or refactoring Elm codebases to leverage OTP. Extends meta-convert-dev with Elm-to-Elixir specific patterns.
arcgis-3d-layers
by SaschaBrunnerCH
3D layer types including VoxelLayer, PointCloudLayer, IntegratedMeshLayer, glTF model imports, and 3D analysis components. Use for volumetric data, LiDAR visualization, and immersive 3D experiences.
ML/AI Skills Conversion Project
by 404kidwiz
Follow the existing patterns to implement these skills.
forge
by jwiegley
Multi-phase, multi-model deep analysis workflow for complex problems. This skill should be used when the user wants rigorous, multi-model collaborative analysis: deep research with Opus and PAL MCP consensus (GPT-5.2-Pro + Gemini 3 Pro), strategic planning, Sonnet execution with tests, comprehensive review, and adversarial devil's advocate critique. Invoke explicitly with /forge.
alba-inertia
by inertia-rails
Alba serializers + Typelizer for type-safe Inertia Rails props with auto-generated TypeScript types. Use when serializing models for Inertia responses, setting up Alba resources, generating TypeScript types from Ruby, or using Inertia prop options (defer, once, merge, scroll) with Alba attributes. Replaces as_json with structured, auto-typed ApplicationResource, page resources, and shared props resources. When active, OVERRIDES the render inertia: { ... } pattern from other skills — use convention-based instance variable rendering instead.
punderstruck
by alexgreensh
Pun expert and comedy brainstorming partner. Discovers wordplay through Datamuse phonetic analysis and structured comedy theory. Use when asking for puns, dad jokes, wordplay, brainstorming creative angles, shower thoughts, roasts, jargon translations, quote remixes, or pun compositions of any length.
checkpoint
by OmniNode-ai
Pipeline checkpoint management for resume, replay, and phase validation
pipeline-audit
by OmniNode-ai
Systematically audit an end-to-end multi-repo pipeline for integration correctness by proving every join between services with file-level evidence, dispatching parallel agents per repo and per proof category, and compiling a severity-ordered gap register with actionable tickets
deslop
by agentika-labs
Remove AI-generated slop from the current branch. Use when the user says "deslop", "remove slop", "clean up AI code", or "remove AI patterns".
Video Editing
by Surojit16
Output: always tell the user the output file path and duration
modelmix
by clasen
Instructions for using the ModelMix Node.js library to interact with multiple AI LLM providers through a unified interface. Use when writing code that calls AI models (OpenAI, Anthropic, Google, Groq, Perplexity, Grok, MiniMax, Fireworks, Together, Lambda, Cerebras, OpenRouter, Ollama, LM Studio), chaining models with fallback, getting structured JSON from LLMs, adding MCP tools, streaming responses, managing multi-provider AI workflows, round-robin load balancing, or rate limiting API requests in Node.js. Also use when the user mentions "modelmix", "ModelMix", asks to "call an LLM", "query a model", "add AI to my app", or wants to integrate any supported provider.
pipeline-metrics
by OmniNode-ai
Report pipeline health metrics — rework ratio, cycle time, CI stability, and feature velocity
crash-recovery
by OmniNode-ai
Show recent pipeline state to orient after an unexpected session end or crash
executing-plans
by OmniNode-ai
Use when partner provides a complete implementation plan to execute — reviews the plan critically, verifies live PR state against plan assumptions, creates Linear tickets via plan-to-tickets, then routes to epic-team (≥3 tickets) or ticket-pipeline (1-2 tickets)
BMAD Method
by daffy0208
Business Model and Architecture Design methodology for aligning technical architecture with business model sustainability and scalability
pipeline
by ElliotJLT
Orchestration pattern for sequential, dependent tasks. When work must flow through stages where each stage depends on the previous (design → implement → test → review), structure as a pipeline with explicit handoffs. Each stage completes before the next begins.
codex
by Zpankz
Execute OpenAI Codex CLI for code analysis, refactoring, and automated editing. Also use for delegating complex debugging and research to GPT models for second opinions.
ctxsift-install
by aakashH242
CtxShift is a skill that helps you focus on your tasks by reducing context clutter and enabling faster state recollections. \
token-optimizer
by Asif2BD
Reduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
multi-model-meta-analysis
by petekp
Synthesize outputs from multiple AI models into a comprehensive, verified assessment. Use when: (1) User pastes feedback/analysis from multiple LLMs (Claude, GPT, Gemini, etc.) about code or a project, (2) User wants to consolidate model outputs into a single reliable document, (3) User needs conflicting model claims resolved against actual source code. This skill verifies model claims against the codebase, resolves contradictions with evidence, and produces a more reliable assessment than any single model.
model-first-reasoning
by petekp
Apply Model-First Reasoning (MFR) to code generation tasks. Use when the user requests "model-first", "MFR", "formal modeling before coding", "model then implement", or when tasks involve complex logic, state machines, constraint systems, or any implementation requiring formal correctness guarantees. Enforces strict separation between modeling and implementation phases.
agent-creation
by joabgonzalez
"Standards-compliant agent definitions with templates. Trigger: When creating agent definitions, setting up project agents, or documenting workflows."
context-engineering
by Zpankz
Understand the components, mechanics, and constraints of context in agent systems. Use when writing, editing, or optimizing commands, skills, or sub-agents prompts.
skill-sync
by joabgonzalez
"Synchronization across model directories. Trigger: After creating or modifying skills, agents, or prompts to sync across directories."