ai-for-science-ascend-tf-community

ai-for-science-ascend-tf-community is a skill for Claude Code from ascend-ai-coding/awesome-ascend-skills. It costs 93 tokens per session (3,565 once invoked), scanned A, original, no licence file.

A migration guide for running TensorFlow 2.x models natively on Huawei Ascend NPU hardware without converting them to PyTorch. It covers source building, plugin installation, automated and manual changes, and accuracy checks.

In plain words
What is it for?
It is for building or adapting TensorFlow 2.x for aarch64 systems, installing the Ascend plugin, migrating models, and verifying their accuracy.
Why use it?
It addresses the work needed when an existing TensorFlow model must run on Ascend hardware while staying in TensorFlow.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the ascend-ai-for-science plugin — 14 skills shipped together , and of ai-for-science

Good fit It is for building or adapting TensorFlow 2.x for aarch64 systems, installing the Ascend plugin, migrating models, and verifying their accuracy.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ascend-ai-coding/awesome-ascend-skills/ascend-tf-community
Install

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.

Any agent
npx skills add ascend-ai-coding/awesome-ascend-skills --skill ascend-tf-community
Clone the repo
git clone --depth 1 https://github.com/ascend-ai-coding/awesome-ascend-skills

Made for: Claude Code.

Or install ascend-ai-for-science, the plugin that ships this one along with the rest of its 14 skills.

Wrote 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.

agentmods badge for ai-for-science-ascend-tf-community

README.md
[![agentmods](https://agentmods.dev/badge/skills/ascend-ai-coding/awesome-ascend-skills/ascend-tf-community/github.svg)](https://agentmods.dev/skills/ascend-ai-coding/awesome-ascend-skills/ascend-tf-community)
Your own site
<a href="https://agentmods.dev/skills/ascend-ai-coding/awesome-ascend-skills/ascend-tf-community"><img src="https://agentmods.dev/badge/skills/ascend-ai-coding/awesome-ascend-skills/ascend-tf-community/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.

agentmods 80×15 button for ai-for-science-ascend-tf-community

Your own site · 80×15
<a href="https://agentmods.dev/skills/ascend-ai-coding/awesome-ascend-skills/ascend-tf-community"><img src="https://agentmods.dev/badge/skills/ascend-ai-coding/awesome-ascend-skills/ascend-tf-community.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,565 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00093 $0.03565
Opus 5.5 $0.00037 $0.01426
Sonnet 5.5 $0.00019 $0.00713
Haiku 4.5 $0.00009 $0.00357

Measured 1mo ago against content hash 1531661932d7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ai-for-science-ascend-tf-community scanned grade A with 1 finding 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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/check_tf_npu_env.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

wget 'https://mirrors.huaweicloud.com/bazel/3.7.2/bazel-3.7.2-linux-arm64' \
skills/ai-for-science/tf-framework/ascend-tf-community/SKILL.md · 370 lines

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.

Read it on GitHub

Files

What ships with it

2 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.

Changes

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.

  1. 1mo ago First seen · 370 lines · 93 tokens per session scan A 1531661932d7

Subscribe to this mod's changes

ai-for-science-ascend-tf-community is a skill published in the GitHub repository ascend-ai-coding/awesome-ascend-skills (177 stars, last pushed today), with no licence file. It adds 93 tokens to every session and 3,565 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.

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