Borrowing it
Nothing to install: this file belongs to supremehui/-Auto-Accounting. 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/supremehui/-Auto-Accounting/main/CLAUDE.mdgit clone --depth 1 https://github.com/supremehui/-Auto-AccountingWrote 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/supremehui/-auto-accounting/claude-md)<a href="https://agentmods.dev/instructions/supremehui/-auto-accounting/claude-md"><img src="https://agentmods.dev/badge/instructions/supremehui/-auto-accounting/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/supremehui/-auto-accounting/claude-md"><img src="https://agentmods.dev/badge/instructions/supremehui/-auto-accounting/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 | $0.00598 | $0.00598 |
| Opus 5.5 | $0.00239 | $0.00239 |
| Sonnet 5.5 | $0.00120 | $0.00120 |
| Haiku 4.5 | $0.00060 | $0.00060 |
Grade A, and why
-Auto-Accounting 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 2mo 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 — 67 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. Communicate in Chinese.
Project Overview
PinMe is an Android app (Kotlin, Jetpack Compose) that captures screenshots via a Quick Settings tile, uses vision LLMs to extract key information (pickup codes, train tickets, verification codes, etc.), and displays results through Flyme Live Notifications (Meizu-specific) or standard notifications plus a home screen widget.
Package: supreme
Min SDK: 33 | Target SDK: 36
Build Commands
Never use ./gradlew build in this project.
Architecture
Core Flow
- QuickCaptureTileService - Quick Settings tile triggers
CaptureActivity - CaptureActivity - Requests MediaProjection permission, captures screen as Bitmap
- ExtractWorkflow - Sends screenshot to vision LLM, parses JSON response
- UnifiedNotificationManager - Shows result via Flyme Live Notification (if available) or standard notification
- PinMeWidget - Glance AppWidget displays recent extractions
Key Components
| Package | Purpose |
|---|---|
capture/ |
Screen capture via MediaProjection API |
extract/ |
LLM workflow and JSON parsing |
vllm/ |
OpenAI-compatible API client (OkHttp) |
notification/ |
Notification handling with Flyme Live Notification support |
widget/ |
Glance AppWidget implementation |
db/ |
Room database for preferences and extraction history |
service/ |
LiveNotification service for Flyme integration |
LLM Configuration
Supports multiple providers configured in Constants.kt:
- 智谱 AI (ZHIPU) - Default, uses
glm-4v-flash - 硅基流动 (SiliconFlow) - Uses
Qwen/Qwen2.5-VL-72B-Instruct - Custom - User-specified OpenAI-compatible endpoint
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.
- 2mo ago First seen · 67 lines · 598 tokens per session scan A 6101679a74d8
-Auto-Accounting CLAUDE.md is an instructions file published in the GitHub repository supremehui/-Auto-Accounting (8 stars, last pushed 9mo ago), licensed Apache-2.0. It adds 598 tokens to every session, about $0.0024 per session on Opus 5.5. 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 2026-09-04.
-Auto-Accounting CLAUDE.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| -Auto-Accounting CLAUDE.mdsupremehui/-Auto-Accounting | Instructions file | 8 | 9mo ago | Apache-2.0 | A | 598 | Claude Code |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |