Agent skills by amd, page 2

Check product pages for a price drop, comparing against the lowest price seen before and alerting only on a new low.

amd/gaia

Recommend films, books, games, restaurants, or gear using what the user has already said they like and dislike, plus a web search for current options.

amd/gaia

Research a topic on the open web and write a cited Markdown report.

amd/gaia

Read an RSS or Atom feed and summarize the newest entries. An agent skill from amd/gaia.

amd/gaia

Check a web page or feed for something worth telling the user about, remembering what was already reported so nothing repeats.

amd/gaia

Summarize a document, meeting transcript, or email — pick a style that matches what the content actually is, and fold long input forward in sections instead of losing the back half.

amd/gaia

Inspect a target ONNX model and prepare metadata for Quark ONNX PTQ planning.

amd/Quark

Enumerate every requested item in long text documents or transcripts, with fields and source evidence.

amd/gaia

How GAIA talks and what it must never claim. An agent skill from amd/gaia.

amd/gaia

The non-obvious invariants of the proactive nightly Claude audit workflow (.github/workflows/claude-nightly-audit.yml): the day-of-week mode selector, the two-key dedup scheme (clusterkey per…

amd/gaia

Pull the concrete commitments out of a thread — who owes what, by when.

amd/gaia

Decide which messages need attention now, which can wait, and which belong to someone else.

amd/gaia

Sort an inbox into what needs a reply, what needs a decision, and what is just noise.

amd/gaia

Turn meeting requests in email into calendar decisions — accept, decline, or propose another time.

amd/gaia

Condense newsletters, promotions, and other bulk mail into one short digest and clear them out.

amd/gaia

Assemble scattered booking confirmations into one chronological itinerary.

amd/gaia

End-to-end ONNX PTQ workflow for AMD Quark — from a .onnx file (and calibration data) to a quantized .onnx output.

amd/Quark

Help a developer report a GAIA TUI, WebUI or agent problem, explicitly share a snapshot with Claude Code or Codex through MCP, and validate isolated worktree fixes.

amd/gaia

Build a Quark ONNX PTQ quantization plan from modelanalysis.json and user intent.

amd/Quark

Validate Quark ONNX quantization output using four lightweight checks: auxiliary file copy alignment, expected non-quantized initializer MD5 byte-identity (inline rawdata + external-data byte…

amd/Quark

Route Quark ONNX user goals to the correct atomic skill. An agent skill from amd/Quark.

amd/Quark

Apply existing ShapeShifter graph passes to an .onnx model via the quark-cli shapeshifter CLI or a ShapeShifter YAML.

amd/Quark

Detect upstream Quark ONNX changes that affect the ONNX skill family and classify required updates.

amd/Quark

Partition an ONNX model graph into named functional subgraphs and emit a subgraphpartition.json file.

amd/Quark

Diagnose failed Quark installation, PTQ execution, script generation, or export attempts.

amd/Quark

Compare skill contracts and guidance against current Quark documentation and source entry points.

amd/Quark

Manually verify that the Quark Agent Skills system behaves correctly across the four contract categories (routing, planning, artifact, recovery).

amd/Quark

Prepare export and downstream evaluation handoff for a planned or completed Quark PTQ run.

amd/Quark

Low-memory file2file quantization for very large safetensors LLMs that cannot be loaded whole.

amd/Quark

Install or verify the correct PyTorch build for a user's accelerator backend before Quark installation.

amd/Quark

L3 recipe that runs a Torch LLM PTQ end-to-end for AMD Quark — for PyTorch / HuggingFace transformers models (safetensors input): quantize → validate → evaluate.

amd/Quark

Torch LLM PTQ workflow for AMD Quark — from model selection to quantized output.

amd/Quark

Inspect a target model and prepare metadata for Quark PTQ planning.

amd/Quark

Build a Quark Torch LLM PTQ quantization plan from model analysis and user intent.

amd/Quark

Validate Quark quantization output using four lightweight checks: auxiliary file copy alignment, excluded tensor MD5 byte-identity, config.json deep comparison after stripping quantization keys, and…

amd/Quark

Route Quark user goals to the correct atomic skill or workflow.

amd/Quark

Route Quark user goals to the correct atomic skill or workflow.

amd/Quark

Detect upstream Quark changes that affect the skill system and classify required updates.

amd/Quark

Validate workspace shape, model paths, output directories, and repo structure before downstream Quark skills proceed.

amd/Quark

A skill your agent uses when integrating the @amd-gaia/gaia npm package — running GAIA's flagship agent, or embedding its local sidecar into a Node, TypeScript, or Electron app.

amd/gaia

Installs or verifies AMD Quark and ensures the selected Python environment has an accelerator-matched PyTorch.

amd/Quark

Runs an end-to-end AMD Quark post-training quantization workflow for PyTorch / Hugging Face LLMs: inspect a Hub or local model, choose a quantization plan, create reproducible artifacts, request…

amd/Quark

End-to-end LLM accuracy evaluation on AMD ROCm (ROCm-only) — container setup, vLLM/SGLang/ATOM serving, lm-eval / lighteval / evalscope benchmarks.

amd/Quark

Shrink a HuggingFace safetensors model to 1 hidden layer for fast debugging without loading the full model into memory.

amd/Quark