Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Add, update, or verify Nexus LLM provider model definitions. Use when adding newly released models, changing OpenAI/OpenRouter/Codex/GitHub Copilot/Anthropic/Google model metadata, updating provider defaults, or live-testing whether a model ID works through the reusable provider smoke test.
Route Quark ONNX user goals to the correct atomic skill. Use when a user describes an ONNX quantization task in plain language — such as "install onnxruntime", "analyze my .onnx model", "choose a preset for my YOLO model", "plan ONNX PTQ", "quantize this .onnx with XINT8/BFP16/MXFP4", "validate my quantized .onnx", "debug a failed ONNX quantization", or any request that involves Quark's ONNX-to-ONNX flow. This is the ONNX-side entry point — trigger it whenever the user's intent involves Quark ONNX and the correct downstream skill is not immediately obvious.
Detect upstream Quark ONNX changes that affect the ONNX skill family and classify required updates. Use when Quark ONNX docs, custom-op registry, quantization config presets, calibration methods, AutoSearchPro presets, ONNX Runtime install matrix, or source behavior under `quark/onnx/` may have drifted from the skill contracts. Trigger for "check if ONNX skills are up to date", "sync ONNX skills with Quark", "has Quark ONNX changed", "update ONNX skills after Quark upgrade", or when ONNX debugging reveals a mismatch between skill instructions and actual `quark.onnx` behavior.
Author or restructure a Quark Agent Skill so it conforms to this project's template, contracts, and layer rules. Use when a maintainer says "create a new skill", "add a skill for X", "scaffold a skill", "draft a SKILL.md", or when an existing skill needs a structural rewrite to match the format contract. Walks the author through capture, draft, test, iterate, and governance handoff. This is a maintainer-facing meta skill, not an end-user PTQ tool.
Route Quark user goals to the correct atomic skill or workflow. Use when a user describes a Quark task in plain language — such as "install Quark", "quantize a model", "analyze my model", "build a PTQ plan", "export the quantized model", "debug a failed run", "run the full PTQ pipeline", "run model quantization", "install Quark", or any request that involves AMD Quark model quantization. This is the entry point skill — trigger it whenever the user's intent involves Quark and the correct downstream skill is not immediately obvious.
End-to-end workflow that creates a skill from a description and attached files, publishes it to Sundial as a private skill, generates a trading card (front + back with QR code), and sends it to a printer. Use when the user wants to create a skill and get a printed trading card, or says "skill to card", "create and print a skill card", "make me a skill with a card".
Parses the natural language task goal to extract actionable sub-objectives and required objects. Trigger this skill whenever a new task is assigned to break down complex instructions into clear, sequential targets. It interprets phrases like 'look at X under Y' to identify target objects (pillow), reference objects (desklamp), and spatial relationships (under).
Places a held object onto or into a target receptacle. Trigger this skill when the agent is carrying an object and needs to deposit it at a specific location to complete a task, such as installing an item on a holder or storing it in a container. It takes the object and destination receptacle as inputs, performing a 'put' action to finalize the object's positioning according to the task goal.
This skill searches for a specific receptacle (e.g., garbage can, cabinet) by systematically exploring the environment, checking multiple locations until found. Trigger when the target receptacle is not initially visible, often after scanning nearby areas. It outputs the receptacle's location and may involve navigating through multiple waypoints.
This skill searches rooms for a liquid source (e.g., sink, toilet, jug) by sequentially surveying different locations. It should be triggered when the task requires obtaining a liquid (like water) and the agent does not have immediate access to it. The skill involves teleporting to candidate rooms, looking around, and identifying potential sources, guiding the agent toward the nearest available liquid.