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 skills add Ascend/agent-skills --skill ascendc-operator-performance-evalgit clone --depth 1 https://github.com/Ascend/agent-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/ascend/agent-skills/ascendc-operator-performance-eval)<a href="https://agentmods.dev/skills/ascend/agent-skills/ascendc-operator-performance-eval"><img src="https://agentmods.dev/badge/skills/ascend/agent-skills/ascendc-operator-performance-eval/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ascend/agent-skills/ascendc-operator-performance-eval"><img src="https://agentmods.dev/badge/skills/ascend/agent-skills/ascendc-operator-performance-eval.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00117 | $0.05425 |
| Opus 5.5 | $0.00047 | $0.02170 |
| Sonnet 5.5 | $0.00023 | $0.01085 |
| Haiku 4.5 | $0.00012 | $0.00543 |
Grade A, and why
ascendc-operator-performance-eval 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 1mo 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 MulanPSL-2.0
The repository is licensed MulanPSL-2.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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.
- examples/layer_norm_profiler_reference/benchmark_layer_norm_torch_npu_profiler.py 4.1 KB runs code
- examples/layer_norm_profiler_reference/layer_norm_perf_cases.jsonl 5.6 KB
- examples/layer_norm_profiler_reference/layer_norm_profiler_common.py 15 KB runs code
- examples/layer_norm_profiler_reference/LAYER_NORM_PROFILER_PERF_GUIDE.md 1.4 KB
- examples/layer_norm_profiler_reference/README.md 686 B
- examples/sample_perf_cases.jsonl 671 B
- examples/sample_report.md 1.4 KB
- references/REFERENCE_JSON_CASE_FORMAT.md 3.9 KB
- references/REFERENCE_PROFILER_AND_METRICS.md 2.5 KB
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.
- 1mo ago First seen · 344 lines · 117 tokens per session scan A a064fec3ec25
ascendc-operator-performance-eval is a skill published in the GitHub repository Ascend/agent-skills (51 stars, last pushed 5mo ago), licensed MulanPSL-2.0. It adds 117 tokens to every session and 5,425 once invoked, about $0.0005 per session on Opus 5.5. 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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