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/aws-samples/sample-sagemaker-agentic-model-deployment/sagemaker-benchmarknpx skills add aws-samples/sample-sagemaker-agentic-model-deployment --skill sagemaker-benchmarkgit clone --depth 1 https://github.com/aws-samples/sample-sagemaker-agentic-model-deploymentWrote 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/aws-samples/sample-sagemaker-agentic-model-deployment/sagemaker-benchmark)<a href="https://agentmods.dev/skills/aws-samples/sample-sagemaker-agentic-model-deployment/sagemaker-benchmark"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-sagemaker-agentic-model-deployment/sagemaker-benchmark.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 | $0.00079 | $0.02185 |
| Opus 5 | $0.00039 | $0.01092 |
| Sonnet 5 | $0.00016 | $0.00437 |
| Haiku 4.5 | $0.00008 | $0.00218 |
Grade A, and why
sagemaker-benchmark 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 3d 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.
The source is not reproduced here
Licensed MIT-0
The repository is licensed MIT-0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
What ships with it
18 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.
- datasets/sharegpt-curated.jsonl 447 KB
- sample-output/benchmark_summary.txt 486 B
- sample-output/failure_reason.txt 100 B
- sample-output/logs/aiperf.log 32 KB
- sample-output/outputs.json 351 KB
- sample-output/plot_generation.log 225 B
- sample-output/plots/aiperf_plot.log 8.7 KB
- sample-output/plots/summary.txt 189 B
- sample-output/plots/ttft_over_time.png 119 KB
- sample-output/plots/ttft_timeline.png 114 KB
- sample-output/profile_export_aiperf.csv 4.0 KB
- sample-output/profile_export_aiperf.json 15 KB
- sample-output/profile_export.jsonl 1251 KB
- sample-output/README.md 1.5 KB
- scripts/benchmark_results.py 9.9 KB runs code
- scripts/benchmark.py 13 KB runs code
- scripts/cloudwatch_metrics.py 4.1 KB runs code
- scripts/config.py 6.1 KB runs code
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.
- 3d ago First seen · 186 lines · 79 tokens per session scan A 8839084280ef
sagemaker-benchmark is a skill published in the GitHub repository aws-samples/sample-sagemaker-agentic-model-deployment (5 stars, last pushed 1mo ago), licensed MIT-0. It adds 79 tokens to every session and 2,185 once invoked, about $0.0004 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 2026-08-31.
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