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 mohitmishra786/low-level-dev-skills --skill arm-svegit clone --depth 1 https://github.com/mohitmishra786/low-level-dev-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/mohitmishra786/low-level-dev-skills/arm-sve)<a href="https://agentmods.dev/skills/mohitmishra786/low-level-dev-skills/arm-sve"><img src="https://agentmods.dev/badge/skills/mohitmishra786/low-level-dev-skills/arm-sve/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/mohitmishra786/low-level-dev-skills/arm-sve"><img src="https://agentmods.dev/badge/skills/mohitmishra786/low-level-dev-skills/arm-sve.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00089 | $0.01782 |
| Opus 5 | $0.00044 | $0.00891 |
| Sonnet 5 | $0.00018 | $0.00356 |
| Haiku 4.5 | $0.00009 | $0.00178 |
Grade A, and why
arm-sve 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 9d 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 — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ARM SVE
Purpose
Guide agents through ARM Scalable Vector Extension (SVE/SVE2) programming: vector-length agnostic (VLA) code, predicate registers, SVE intrinsics via <arm_sve.h>, runtime vector length with svcnt, compiler flags, platform differences (Graviton3, Apple M4), and GDB debugging of SVE registers.
When to Use
- Writing high-performance SIMD on AArch64 servers (AWS Graviton3/4)
- Porting fixed-width NEON code to length-agnostic SVE
- Using predicate masks for loop tails instead of separate cleanup loops
- Auto-vectorizing with GCC/Clang
-march=armv9-a+sve2 - Debugging SVE register state in GDB on hardware with SVE support
- Exploiting SVE2 dot product and crypto extensions
Workflow
1. SVE vs NEON
| NEON | SVE/SVE2 | |
|---|---|---|
| Vector width | Fixed (128-bit) | Scalable (128–2048 bits, hardware dependent) |
| Predication | Limited | Full predicate registers P0–P15 |
| Portability across ARM CPUs | Same width everywhere | VLA — adapts to hardware VL |
| Apple Silicon | Always available | M4+ has SVE2 |
2. Predicate and VLA concepts
SVE registers
├── Z0–Z31 — scalable vector data registers
└── P0–P15 — predicate (mask) registers
Vector Length (VL) — determined at runtime per CPU
svcntb() → bytes per vector
svcntw() → 32-bit elements per vector
Code written once runs at full width on any SVE-capable CPU.
3. SVE intrinsics example
#include <arm_sve.h>
#include <stddef.h>
void saxpy_sve(float *y, const float *x, float alpha, size_t n) {
svbool_t pg = svwhilelt_b32(0, n);
size_t i = 0;
do {
svfloat32_t vx = svld1_f32(pg, &x[i]);
svfloat32_t vy = svld1_f32(pg, &y[i]);
vy = svmla_n_f32_x(pg, vy, vx, alpha); // y += alpha * x
svst1_f32(pg, &y[i], vy);
i += svcntw(); // advance by vector length in 32-bit elements
pg = svwhilelt_b32(i, n);
} while (svptest_any(svptrue_b32(), pg));
}
gcc -march=armv9-a+sve2 -O3 -o saxpy saxpy.c
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.
- 9d ago First seen · 191 lines · 89 tokens per session scan A d4cbee608bf2
arm-sve is a skill published in the GitHub repository mohitmishra786/low-level-dev-skills (203 stars, last pushed 2mo ago), licensed MIT. It adds 89 tokens to every session and 1,782 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 2026-09-03.
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