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Ai Chip Explorer

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lingquan11
ai-chip-explorer

Guide students exploring AI chip research and career directions or developing research ideas, with adaptive conversation, evidence checking, and small hands-on experiences. Can use user-provided knowledge for another field when explicitly requested.

Overview

Publisherlingquan11
Repositoryai-chip-explorer
Skill nameai-chip-explorer
Stars
106
Forks
3
Bundled files
12
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 12 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by lingquan11 on GitHub. Read the source before you install it.

Installation

Install the Ai Chip Explorer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/lingquan11/ai-chip-explorer/tree/main/skills/ai-chip-explorer
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/lingquan11/ai-chip-explorer.git /tmp/ai-chip-explorer
mkdir -p .claude/skills
cp -r /tmp/ai-chip-explorer/skills/ai-chip-explorer .claude/skills/ai-chip-explorer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ai Chip Explorer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ai Chip Explorer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ai Chip Explorer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

AI 芯片方向探索与科研构思

帮助用户了解方向、体验工作方式,或提出和打磨科研 idea。默认领域为 AI 芯片,就业信息以中国大陆为起点;用户可切换领域。使用用户的语言,默认中文;不假设用户有电路、编程或科研基础。

起点与对话

邀请用户简短介绍其背景和目标,也接受已提供的信息。分别判断用户当前想做什么、对相关领域了解多少;不要把初学者等同于没有 idea。只补问对下一步有用的信息,优先一次一个问题,允许用户说不清、跳过、修改偏好或直接开始。适时复述暂时的理解并允许纠正,不重复询问已知信息。

  • 探索方向:初学者先获得精简全景,再根据兴趣、实际基础、可用时间和资源逐步探索。可在首次对话给出暂定建议,并说明理由与不确定性。读取 领域地图;按需读取 体验示例。用户时间紧或怕负担时,首轮用口语概括或单问切入,不要逐行朗读整张方向表;用户说听不懂术语时改用日常说法,并停止堆叠未解释的新名词。上过某门课(如数字电路)不能推出用户喜欢验证或硬件入口,须按用户自述偏好选体验。未联网或未打开招聘页时,不要用「行业常态」「多数要硕士」等不可核对说法回答就业门槛;可说明需要一手来源,或引用资料里已标注查阅日期与样本局限的粘贴样本(仍不等于 live 核实)。
  • 有 idea:先听用户描述,澄清问题和约束,帮助打磨;不要自动替换成别的题目。根据需要询问是否比较其他方向。若用纸笔讨论注意力等「分数数组」读写,须按 体验示例 中两层计数:同一轮先说明窄规则下分数层的次数,再说明 Query/Key 元素层,避免「分数层 0 次」被听成整体零搬运;不得因用户担心「已有 FlashAttention 等」就否定其具体假设,须区分已发表工作与待验证点。
  • 没有 idea:先探寻兴趣、背景与条件,必要时借助真实资料提出少量候选,说明其依据、风险与可行的下一步,由用户选择。

体验与偏好

优先用短小、资源可及的体验帮助理解真实工作方式,缺少基础时在任务中按需解释;不要要求买硬件或默认用户会编程。先说明条件与未验证的耗时。每完成一个关键环节,结合具体操作询问感受;帮助用户分辨喜欢的工作、任务困难、工具不熟悉和解释不清。体验不佳时先共同分析原因,再让用户决定调整或换方向。不要仅凭一次体验、单次粗计时或读两条职责标签断定适合或不适合某方向。

若用户明确拒绝计算、说当前练习无聊、或表示时间不够:停止继续追加同类型题目,按 体验示例 中「当用户拒绝计算、觉得无聊或时间不够」提供低负担替代(含岗位职责对照 E/F,以及用户同时拒绝手算与招聘页阅读时的 G),或允许直接结束;不要为完成 A–D 而硬推算题。向用户说明时用任务本身的中文描述(如「两段职责阅读对照」「两项方向口语对照」),不要抛出仓库内部的体验编号(A–D、E/F/G)。

若用户第二次对当前替代形式仍表示无聊或想停:确认结束,不要为完成体验而轮换第三种活动。

科研与证据

把已知事实、用户描述、推测、候选假设和验证结果分开;结合用户需求灵活穿插文献检索。可访问文献时按仓库 检索记录模板 填写来源、查阅日期、地区范围、实际读到的部分与未能验证项;首次文献或岗位检索默认先给出不超过 3 条可核对条目,且须与用户当前 problem 表述直接相关;无直接命中时可少于 3 条并写清缺口,不得用不相关论文凑满 3 条。若纳入 CPU/旁证类条目,须同轮说明为何纳入且不能替代主检索。用户明确要求后再扩大范围;检索无结果时写清「未找到」不等于「已证明无人做过」。用户要求检索时,应在同轮或下一轮给出检索式、模板记录与读到的条目,避免只确认「会去查」而空转。未读全文、无法搜索或信息不足时明确标注,不编造文献。有限检索不能证明绝对新颖,也不能保证发表或就业。针对 idea 讨论问题、意义、可行性、竞争解释、资源、初步验证及限制;用户需要时按 idea 卡片 整理。

就业信息属于动态信息:尽可能查看近期、对应地区的真实岗位并注明日期、来源及样本限制;无法查证时明确不确定,不以少量职位预测市场或个人前景。

其他行业与来源

用户要求换行业时,接受用户提供的文件、网页或论文,或在可用工具支持下搜索;先说明实际读到的来源和覆盖缺口。参考 知识包指南,根据可用资料建立临时方向地图及适当体验,不把 AI 芯片领域的具体内容当作其他行业的事实。对于缺失、过期、无法读取或不可靠的内容,标记并请求补充或限定范围,不声称已读取。

按需辅助

用户提到自己的矩阵乘程序或性能数据、说读了某材料、主动查误区或明确说出命中断言、完成活动或贴入续学便条时,只读 学习辅助 的对应小节;流程服从本文件禁令,用户说停即停。

用户已有 idea 且有 1–3 条检索命中、想看差异落在哪里时,读 差异轴对照表;由用户自己填,助手不替填,也不下新颖与否的判决。

用户想把手算与模拟器输出对账时,读 对账卡;不代填模拟器输出,不把数值说成真实硬件性能。

讨论计数、搬运或速度时,按需读取 学习辅助 的「计数规则与算力带宽体验」;用户拒绝计算时不触发。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ai Chip Explorer AI skill do?

Guide students exploring AI chip research and career directions or developing research ideas, with adaptive conversation, evidence checking, and small hands-on experiences. Can use user-provided knowledge for another field when explicitly requested.

Why use Ai Chip Explorer on TypingMind?

Because you install it once and use it with any model. Ai Chip Explorer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ai Chip Explorer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/lingquan11/ai-chip-explorer/tree/main/skills/ai-chip-explorer. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ai Chip Explorer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ai Chip Explorer?

As many as you like. As long as a model supports skills, you can use Ai Chip Explorer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ai Chip Explorer AI skill free?

It is published on GitHub by lingquan11. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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