Borrowing it
Nothing to install: this file belongs to flanliulf/AI-Copyright-Application-Generator. 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/flanliulf/AI-Copyright-Application-Generator/main/CLAUDE.mdgit clone --depth 1 https://github.com/flanliulf/AI-Copyright-Application-GeneratorWrote 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/flanliulf/ai-copyright-application-generator/claude-md)<a href="https://agentmods.dev/instructions/flanliulf/ai-copyright-application-generator/claude-md"><img src="https://agentmods.dev/badge/instructions/flanliulf/ai-copyright-application-generator/claude-md/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/instructions/flanliulf/ai-copyright-application-generator/claude-md"><img src="https://agentmods.dev/badge/instructions/flanliulf/ai-copyright-application-generator/claude-md.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 | $0.03785 | $0.03785 |
| Opus 5 | $0.01893 | $0.01893 |
| Sonnet 5 | $0.00757 | $0.00757 |
| Haiku 4.5 | $0.00379 | $0.00379 |
Grade A, and why
AI-Copyright-Application-Generator 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 320 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides comprehensive guidance to Claude Code (claude.ai/code) when working with this advanced AI-driven software copyright materials generation system.
Project Overview & Strategic Vision
This repository contains a revolutionary AI-driven Software Copyright Application Materials Generation System - a pioneering platform that democratizes professional intellectual property protection through systematic knowledge engineering and AI-powered automation.
Core Innovation & Value Proposition
This system represents a paradigm shift in software copyright application preparation:
- Knowledge Systematization: Transforms expert-level copyright application knowledge into reusable, automated AI instructions
- Professional Capability Democratization: Enables developers of all experience levels to generate professional-grade copyright materials
- Vertical AI Application Pioneer: First comprehensive application of AI prompt engineering in the software copyright domain
- Multi-dimensional Standardization: Systematic standardization across UI design, technical architecture, and documentation formats
System Architecture & Core Components
The system implements a three-tier knowledge-driven architecture:
1. Knowledge Layer (Expert Knowledge Systematization)
- AI Prompt Engineering Suite: Eight specialized prompts encoding domain expertise
- UI Design Knowledge Base: Twelve comprehensive design systems covering diverse aesthetic paradigms
- Technical Standards Repository: Modular technology stack specifications and compliance frameworks
- Quality Assurance Protocols: Embedded validation and verification mechanisms
2. Processing Layer (Intelligent Generation Engine)
- Progressive Construction Pipeline: Optimized six-stage workflow from conceptualization to delivery (upgraded from previous 8-stage process)
- 阶段1：项目初始化和系统架构设计
- 阶段2：产品规划和界面设计
- 阶段3：前端开发实现
- 阶段4：后端系统开发
- 阶段5：软著申请文档生成
- 阶段6：材料整理和质量验收
- Multi-modal Content Generation: Coordinated creation of documentation, code, and visual specifications
- Context-Aware Customization: Dynamic adaptation based on project requirements and user preferences
- Quality Control Integration: Real-time validation against copyright office standards
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.
- 10d ago First seen · 320 lines · 3,785 tokens per session scan A 478413caaafe
AI-Copyright-Application-Generator CLAUDE.md is an instructions file published in the GitHub repository flanliulf/AI-Copyright-Application-Generator (91 stars, last pushed 1y ago), licensed Apache-2.0. It adds 3,785 tokens to every session, about $0.0189 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.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.