AI Fundamentals is a learning resource about the foundations and infrastructure behind artificial intelligence, including GPU architecture, CUDA programming, large language models, AI systems, and related operations. It is intended for AI engineers, system architects, GPU developers, application developers, and researchers. The catalogue add-ons support learning or working with these AI infrastructure topics.
Borrowing it
Nothing to install: this file belongs to ForceInjection/AI-fundamentals. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ForceInjection/AI-fundamentals/main/CLAUDE.mdgit clone --depth 1 https://github.com/ForceInjection/AI-fundamentalsWrote 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/instructions/forceinjection/ai-fundamentals/claude-md)<a href="https://agentmods.dev/instructions/forceinjection/ai-fundamentals/claude-md"><img src="https://agentmods.dev/badge/instructions/forceinjection/ai-fundamentals/claude-md.svg" alt="Measured on agentmods" 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 | $0.02172 | $0.02172 |
| Opus 5 | $0.01086 | $0.01086 |
| Sonnet 5 | $0.00434 | $0.00434 |
| Haiku 4.5 | $0.00217 | $0.00217 |
Grade A, and why
AI-fundamentals CLAUDE.md 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 7d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- forceinjection.github.io CLAUDE.md — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Repository overview
AI Fundamentals is a Chinese-language knowledge repository covering the full AI infrastructure stack: GPU architecture, CUDA programming, LLM theory, inference systems, cloud-native AI platforms, agentic systems, RAG, and more. All content is authored in Markdown.
- License: Apache 2.0
- Content is organized in semantically numbered top-level directories (
01_hardware_architecture/through11_ai_native_everything/, plus98_llm_programming/and99_misc/). Each directory corresponds to a major topic area with its ownREADME.mdportal. 02_dpu_programming/、02_gpu_programming/和02_npu_programming/share the02_prefix — all three are sub-modules under "底层计算与异构编程."AGENTS.mdexists alongside this file and covers module-level architecture details for GitHub Copilot. This file focuses on project-level conventions that apply to all work in the repo.
Commit conventions
This repo uses Conventional Commits with Chinese descriptions:
docs(scope): description
chore(scope): description
refactor(scope): description
feat(scope): description
Scopes are derived from directory/topic areas. Common scopes seen in the history: readme, dpu, gpu, npu, training, llm-theory, rag, graph_rag, agentic, agent_infra, inference, kv_cache, vllm, reference_design, storage, gpu_manager, k8s, course, trae, multi_agent, ai-native, smart_customer_service, kvbm, submodule. Look at git log --oneline for recent examples before committing.
File conventions
- All top-level topic directories use zero-padded numeric prefixes (e.g.,
01_,02_,03_) to maintain ordering. - Within a topic directory, files may use numeric prefixes for ordering (e.g.,
01_concepts.md,02_practice.md). - Translated content appends a language suffix to the filename (e.g.,
file.zh-CN.md). - Image assets live in
img/at the repo root, or alongside the files that reference them within topic subdirectories. - Interactive HTML visualizations (e.g., inference pipeline demos) are placed alongside the markdown documents they complement, in the same topic subdirectory.
README.mdfiles at directory roots serve as navigation portals and contain link trees to content within that directory. When adding a new article, you must update the corresponding directory'sREADME.mdportal to include a link to the new file — this is the primary navigation mechanism for readers.
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.
- 7d ago First seen · 132 lines · 2,172 tokens per session scan A 326eb8767b4e
AI-fundamentals CLAUDE.md is an instructions file published in the GitHub repository ForceInjection/AI-fundamentals (2,542 stars, last pushed today), licensed Apache-2.0. It adds 2,172 tokens to every session, about $0.0109 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 2026-08-30.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.