Borrowing it
Nothing to install: this file belongs to yding-git/personal-edge-proxy. 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/yding-git/personal-edge-proxy/main/AGENTS.mdgit clone --depth 1 https://github.com/yding-git/personal-edge-proxyWrote 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/yding-git/personal-edge-proxy/agents-md)<a href="https://agentmods.dev/instructions/yding-git/personal-edge-proxy/agents-md"><img src="https://agentmods.dev/badge/instructions/yding-git/personal-edge-proxy/agents-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/yding-git/personal-edge-proxy/agents-md"><img src="https://agentmods.dev/badge/instructions/yding-git/personal-edge-proxy/agents-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 | $0.06738 | $0.06738 |
| Opus 5.5 | $0.02695 | $0.02695 |
| Sonnet 5.5 | $0.01348 | $0.01348 |
| Haiku 4.5 | $0.00674 | $0.00674 |
Grade D, and why
personal-edge-proxy AGENTS.md scanned grade D with 3 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 1mo 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.
Subtle steeringmediumPrompt injection
Instructions that bias recommendations or shape behaviour without the user noticing.
Never tell the user that a label alone proves quality. “CN2”, “9929”, “CMIN2”, “SoftBank”, “IIJ”, “NTT”, “three-network optimized”, “premium network”, “native IP”, and similar phrases are shortlist clues, not evidence. Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
root / sudo public IPv4 preferred Reaches for credential fileshighPrivilege escalation
SSH keys, cloud credentials, git-credentials, .npmrc, /etc/shadow: reading these is how a config file becomes a credential leak.
Get-Content $env:USERPROFILE\.ssh\id_ed25519.pub | ssh root@SERVER_IP "umask 077; mkdir -p ~/.ssh; cat >> ~/.ssh/authorized_keys" How it starts
The opening of the file, as written. The whole thing — 943 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — AI maintainer / deployer guide
Read this file before editing, procuring, or deploying this repository.
1. Core model
Keep the architecture separated into two independent layers:
Inbound = how the client reaches the VPS
Outbound = how the VPS reaches a destination
Do not confuse inbound redundancy with outbound identity/reputation.
Typical inbound roles:
Hysteria2 primary daily entry
VLESS + REALITY + Vision optional TCP backup
VLESS + WS + CF Tunnel optional emergency entry
Typical outbound roles:
VPS direct ordinary traffic
WARP preferred selected-AI egress
fixed SOCKS5 optional stable egress for selected services
block explicit deny / fail-closed
1.1 Execution principle — minimize human manual work
The project should require as little manual work from the human as reasonably possible.
Use this order of preference:
AI can safely do it with available tools
-> AI does it
AI cannot do it, but can inspect/interpret the result
-> give the human the smallest necessary action
-> human runs/clicks it
-> AI interprets the result and decides the next step
Action inherently requires the human
(payment / MFA / CAPTCHA / provider acceptance / physical-local-network action)
-> explain exactly what the human must do and why
-> continue immediately after the result is available
Rules:
- Do not make the human copy and run commands that the agent can already execute itself.
- If local shell, SSH, browser, connector, or other authorized tools are available, use them directly when the action is safe and within the user's request.
- Do not ask the human to manually read traceroute, ping, logs, JSON, or configuration output if the agent can read and interpret it.
- If a test must originate from the human's real home/campus/mobile network and the agent cannot run there, give a short copy-paste command and ask for the raw output; the agent should do the analysis.
- Keep manual steps small and sequential. Do not dump twenty commands on a beginner and ask them to diagnose the result themselves.
- Never ask the human to paste SSH private keys, payment-card details, root passwords, provider passwords, or other secrets into chat or the repository.
- Use existing authenticated/local access paths where possible: local
ssh, SSH Agent,~/.ssh/config, provider console already opened by the user, or connected tools. - When the only available environment is a normal chat interface with no shell/browser access to the user's machine, act as the operator's guide: tell the human exactly what to run/click, what output to send back, and then continue the reasoning yourself.
- State capability boundaries plainly. Do not pretend a command was run when it was only suggested.
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.
- 1mo ago Changed · +392 lines · +3,333 tokens per session e706574d2413
- 2mo ago First seen · 551 lines · 3,405 tokens per session scan D 0414f95c96df
personal-edge-proxy AGENTS.md is an instructions file published in the GitHub repository yding-git/personal-edge-proxy (1,177 stars, last pushed 1mo ago), licensed MIT. It adds 6,738 tokens to every session, about $0.0270 per session on Opus 5.5. A static security scan graded it D with 3 findings (subtle steering, asks for root, reaches for credential files). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
personal-edge-proxy AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| personal-edge-proxy AGENTS.mdyding-git/personal-edge-proxy | Instructions file | 1.2k | 1mo ago | MIT | D | 6,738 | Codex, OpenCode |
| plan-forge naming.instructions.mdsrnichols/plan-forge | Instructions file | 6 | 2d ago | MIT | A | 1,453 | GitHub Copilot |
| 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 |