kernel-designer

kernel-designer is a skill for Claude Code, OpenCode from mindspore-ai/akg. It costs 81 tokens per session (2,625 once invoked), scanned A, original, Apache-2.0.

An algorithm-sketch design tool for computational operators. It produces high-level pseudocode and implementation guidance for several programming and hardware languages.

In plain words
What is it for?
It designs new operator algorithms, improves earlier sketches using performance history, and can provide parameter ranges in hint mode.
Why use it?
It helps developers decide how an operator should work and where parallel processing, memory improvements, or loop changes may help before writing the final code.

Skill for Claude CodeOpenCode

Written for Claude Code and OpenCode: argument-hint in frontmatter, but also installed under .opencode/.

Good fit It designs new operator algorithms, improves earlier sketches using performance history, and can provide parameter ranges in hint mode.

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Install with agentmods
npx agentmods add skills/mindspore-ai/akg/kernel-designer
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 mindspore-ai/akg --skill kernel-designer
Clone the repo
git clone --depth 1 https://github.com/mindspore-ai/akg

Made for: Claude Code, OpenCode.

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 kernel-designer

README.md
[![agentmods](https://agentmods.dev/badge/skills/mindspore-ai/akg/kernel-designer/github.svg)](https://agentmods.dev/skills/mindspore-ai/akg/kernel-designer)
Your own site
<a href="https://agentmods.dev/skills/mindspore-ai/akg/kernel-designer"><img src="https://agentmods.dev/badge/skills/mindspore-ai/akg/kernel-designer/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 kernel-designer

Your own site · 80×15
<a href="https://agentmods.dev/skills/mindspore-ai/akg/kernel-designer"><img src="https://agentmods.dev/badge/skills/mindspore-ai/akg/kernel-designer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 81 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,625 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Agent Snooping · line 49
    Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.
    Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
  • medium Agent Snooping · line 57
    Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.
    Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
How audits are shown
Origin original 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 $0.00081 $0.02625
Opus 5 $0.00041 $0.01313
Sonnet 5 $0.00016 $0.00525
Haiku 4.5 $0.00008 $0.00263

Measured 9d ago against content hash 51cac3071d11, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

kernel-designer 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.

akg_agents/workspace/.opencode/skills/kernel-designer/SKILL.md · 177 lines

How it starts

The opening of the file, as written. The whole thing — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.

算子算法草图设计 Skill

设计原则:

  • 设计清晰的、可理解的算法流程
  • 遵循 DSL 和硬件特性的最佳实践
  • 考虑目标硬件架构的优化机会(并行度、内存访问模式)
  • 标注优化点和权衡决策

草图应具备:高层抽象(关注算法逻辑和优化策略,而非实现细节)、易于理解(便于 Coder 转换为可执行代码)、包含优化提示(标注并行化、内存优化、循环展开等机会)。

工作模式

本 skill 根据输入自动判断工作模式:

模式 触发条件 行为
首次设计 inspirations 加载参考文档 → 分析任务 → 生成草图
进化优化 inspirations 加载参考文档 → 分析历史草图性能 → 生成优化后的草图
Hint 模式 enable_hint_mode 且 task_desc 含 hint 标记 加载参考文档 → 分析任务 → 生成草图 + 参数空间配置(JSON 输出)

设计流程

Step 1: 加载参考文档

根据 archdsltask_desc 参数,用 read 工具读取参考文档。

本 skill 加载后,<base_url> 标签提供 skill 目录路径(记为 $SD)。所有参考文档路径基于 $SD/references/

1.1 Sketch DSL 规范(必选)

始终加载:

$SD/references/designer-skills/sketch-design/SKILL.md
1.2 Hint 模式指南(条件加载)

enable_hint_mode 为 true 且 task_desc 中包含 hint 标记(@hint:@range_hint@elemwise_hint 等)时加载:

$SD/references/designer-skills/hint-mode/SKILL.md

⚠️ 参考文档路径下的文件虽然名为 SKILL.md,但在此上下文中它们是参考内容文件。请使用 read 工具按文件路径读取,不要使用 skill 工具加载。

1.3 硬件规格

路径:$SD/references/hardware/{文件名}

arch 前缀 文件名
a100 CUDA_A100.md
h20 CUDA_H20.md
l20 CUDA_L20.md
rtx3090 CUDA_RTX3090.md
ascend910b1 Ascend910B1.md
ascend910b2 Ascend910B2.md
ascend910b2c Ascend910B2C.md
ascend910b3 Ascend910B3.md
ascend910b4 Ascend910B4.md
ascend310p3 Ascend310P3.md
ascend910_9362 Ascend910_9362.md
ascend910_9372 Ascend910_9372.md
ascend910_9381 Ascend910_9381.md
ascend910_9382 Ascend910_9382.md
ascend910_9391 Ascend910_9391.md
ascend910_9392 Ascend910_9392.md
ascend950dt_95a Ascend950DT_95A.md
ascend950pr_950z Ascend950PR_950z.md
ascend950pr_9572 Ascend950PR_9572.md
ascend950pr_9574 Ascend950PR_9574.md
ascend950pr_9575 Ascend950PR_9575.md
ascend950pr_9576 Ascend950PR_9576.md
ascend950pr_9577 Ascend950PR_9577.md
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ascend950pr_957d Ascend950PR_957d.md
ascend950pr_9581 Ascend950PR_9581.md
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ascend950pr_9589 Ascend950PR_9589.md
ascend950pr_958a Ascend950PR_958a.md
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ascend950pr_9599 Ascend950PR_9599.md

Read the full file on GitHub · 177 lines

Files

What ships with it

4 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. 9d ago First seen · 177 lines · 81 tokens per session scan A 51cac3071d11

Subscribe to this mod's changes

kernel-designer is a skill published in the GitHub repository mindspore-ai/akg (259 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 81 tokens to every session and 2,625 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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