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-ai-coding/awesome-ascend-skills --skill ascend-transformer-boostgit clone --depth 1 https://github.com/ascend-ai-coding/awesome-ascend-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-ai-coding/awesome-ascend-skills/ascend-transformer-boost)<a href="https://agentmods.dev/skills/ascend-ai-coding/awesome-ascend-skills/ascend-transformer-boost"><img src="https://agentmods.dev/badge/skills/ascend-ai-coding/awesome-ascend-skills/ascend-transformer-boost/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-ai-coding/awesome-ascend-skills/ascend-transformer-boost"><img src="https://agentmods.dev/badge/skills/ascend-ai-coding/awesome-ascend-skills/ascend-transformer-boost.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 | $0.00098 | $0.02449 |
| Opus 5 | $0.00049 | $0.01224 |
| Sonnet 5 | $0.00020 | $0.00490 |
| Haiku 4.5 | $0.00010 | $0.00245 |
Grade A, and why
external-gitcode-ascend-ascend-transformer-boost 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 8d 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
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
What ships with it
3 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.
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.
- 8d ago First seen · 201 lines · 98 tokens per session scan A f8078db8b8d0
external-gitcode-ascend-ascend-transformer-boost is a skill published in the GitHub repository ascend-ai-coding/awesome-ascend-skills (167 stars, last pushed yesterday), with no licence file. It adds 98 tokens to every session and 2,449 once invoked, about $0.0005 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.
Other skills, from other repositories
ascend-transformer-boost
An index of skills for developing with Huawei’s Ascend Transformer Boost (ATB) library. It groups eight skills covering CANN setup, ATB testing, operator replacement design, and migration to ACLNN for Ascend NPU development.
atb-aclnn-operator-migration
A workflow for migrating ATB operators to ACLNN on Huawei Ascend 910B and 950 devices. ATB and ACLNN are libraries for implementing computations on Ascend hardware.
atb-nnal-installer
An installation guide for the Ascend NPU NNAL acceleration library. It handles installing the NNAL package, setting its environment variables, and checking that it works.
atb-debug-guide
A troubleshooting guide for ATB operator tests and setup. ATB is a software environment for testing computing operators, and an operator is a small piece of a machine-learning or numerical program.
ascend-docker
Create Docker containers for Huawei Ascend NPU development with proper device mappings and volume mounts. Use when setting up Ascend development environments in Docker, running CANN applications in containers, or creating isolated NPU development workspaces. Supports privileged mode (default), basic mode, and full…
cann-nnal-installer
An installation guide for Huawei Ascend CANN, a software toolkit for running applications on Ascend neural-processing hardware. It covers the CANN Toolkit, kernels, and NNAL components.