Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/amd/skills/magpie-kernel-evaluatornpx skills add amd/skills --skill magpie-kernel-evaluatorgit clone --depth 1 https://github.com/amd/skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/amd/skills/magpie-kernel-evaluator)<a href="https://agentmods.dev/skills/amd/skills/magpie-kernel-evaluator"><img src="https://agentmods.dev/badge/skills/amd/skills/magpie-kernel-evaluator.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00127 | $0.01679 |
| Opus 5 | $0.00063 | $0.00839 |
| Sonnet 5 | $0.00025 | $0.00336 |
| Haiku 4.5 | $0.00013 | $0.00168 |
Grade A, and why
magpie-kernel-evaluator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Magpie
Use Magpie for three connected jobs:
- Benchmark an inference workload and collect throughput, latency, and traces.
- Analyze or compare GPU kernels for correctness and performance.
- Drive an optimization loop from a benchmark bottleneck to source, candidate kernels, and end-to-end validation.
Describe only capabilities supported by the checked-out Magpie version. Do not infer support for an unverified ROCm, GPU, framework, or experimental integration.
Choose the workflow
| User goal | Workflow |
|---|---|
| Evaluate one implementation | analyze |
| Rank two or more implementations | compare |
| Measure model-serving performance | benchmark |
| Find expensive kernels in existing traces | standalone gap analysis |
| Explain a profiled inference workload | benchmark → TraceLens post-processing → stage/roofline review |
| Optimize an end-to-end workload | benchmark → TraceLens/gap analysis → source mapping → analyze/compare → re-benchmark |
Use a YAML config for reproducible or multi-step work. Use inline CLI arguments for small exploratory runs.
Preflight
-
Locate the Magpie repository or installed package.
-
Check the local interface before constructing commands:
magpie --help magpie analyze --help magpie compare --help magpie benchmark --help magpie --gpu-info -
Check required tools, model access, GPU visibility, writable output space, and container or Ray access as applicable.
-
Read the repository compatibility matrix before making version claims. Treat ROCm or hardware not listed there as unverified until tested.
-
Record the exact config, model revision, image, environment variables, GPU allocation, and Magpie commit for benchmark comparisons.
Run from the Magpie repository root, install with pip install -e ., or use python -m Magpie when the magpie entry point is unavailable.
Analyze a kernel
Prefer a config when correctness or profiler settings matter:
magpie analyze --kernel-config path/to/kernel.yaml
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- .federated.json 222 B
- evals/evals.json 4.6 KB
- evals/files/analyze-simple-hip/examples/simple_hip_test/analyze_default.yaml 413 B
- evals/files/analyze-simple-hip/examples/simple_hip_test/vector_add.hip 1.7 KB
- evals/files/compare-hip-variants/baseline/vector_add.hip 1.7 KB
- evals/files/compare-hip-variants/candidate/vector_add.hip 1.8 KB
- examples.md 4.9 KB
- reference.md 9.7 KB
- skill-card.md 458 B
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 150 lines · 127 tokens per session scan A f5cb65304477
magpie-kernel-evaluator is a skill published in the GitHub repository amd/skills (327 stars, last pushed 2d ago), licensed MIT. It adds 127 tokens to every session and 1,679 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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