Borrowing it
Nothing to install: this file belongs to lwmxiaobei/xbcode. 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/lwmxiaobei/xbcode/main/AGENTS.mdgit clone --depth 1 https://github.com/lwmxiaobei/xbcodeWrote 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/lwmxiaobei/xbcode/agents-md)<a href="https://agentmods.dev/instructions/lwmxiaobei/xbcode/agents-md"><img src="https://agentmods.dev/badge/instructions/lwmxiaobei/xbcode/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/lwmxiaobei/xbcode/agents-md"><img src="https://agentmods.dev/badge/instructions/lwmxiaobei/xbcode/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 | $0.00634 | $0.00634 |
| Opus 5.5 | $0.00254 | $0.00254 |
| Sonnet 5.5 | $0.00127 | $0.00127 |
| Haiku 4.5 | $0.00063 | $0.00063 |
Grade A, and why
xbcode AGENTS.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 — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
This file provides guidance to Codex (Codex.ai/code) when working with code in this repository.
Project Overview
A TypeScript CLI agent (similar to Codex) built with OpenAI SDK + Ink (React for CLI). It implements an agent loop with tool use, streaming output, and a terminal UI.
Commands
npm run dev # Run in development (tsx, no compile)
npm run build # Compile TypeScript to dist/
npm start # Run compiled output
Architecture
Multi-file architecture: src/index.tsx (UI), src/agent.ts (agent loop), src/tools.ts (tool definitions & handlers), src/types.ts, src/todo.ts.
Dual API mode: Supports both OpenAI Responses API (default) and Chat Completions API (for DeepSeek-compatible endpoints). Auto-detected via OPENAI_BASE_URL or set explicitly with OPENAI_API_MODE.
Agent loop: agentLoop() (Responses API) and agentLoopWithChatCompletions() (Chat Completions) implement the core think-act cycle. Both loop until LLM returns no tool calls.
Tools: 5 built-in tools — bash, read_file, write_file, edit_file, task. The task tool dispatches work to an independent sub-agent with a clean context (no parent history). Sub-agents have base tools only (no recursive task). Max 30 rounds per sub-agent. All tools return strings (errors included). Tool schema uses JSON Schema format with additionalProperties: false.
UI layer: React components rendered via Ink. UiBridge interface connects agent logic to UI updates (streaming deltas, tool call display).
State: AgentState holds previousResponseId (Responses API chain) or chatHistory (Chat Completions message array).
Environment Variables
Configure in .env at project root:
OPENAI_API_KEY— requiredMODEL_ID— defaultgpt-4.1OPENAI_BASE_URL— optional, for compatible endpointsOPENAI_API_MODE—responsesorchat-completions(auto-detected)SHOW_THINKING=1— display model reasoningREASONING_EFFORT— thinking intensity for reasoning models (minimal/low/medium/high/xhigh/max)
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 · 49 lines · 634 tokens per session scan A 33a31e16b443
xbcode AGENTS.md is an instructions file published in the GitHub repository lwmxiaobei/xbcode (48 stars, last pushed 2mo ago), licensed MIT. It adds 634 tokens to every session, about $0.0025 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 2026-08-30.
xbcode AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| xbcode AGENTS.mdlwmxiaobei/xbcode | Instructions file | 48 | 2mo ago | MIT | A | 634 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | yesterday | 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 |