Borrowing it
Nothing to install: this file belongs to lululu811/zettaranc-skill. 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/lululu811/zettaranc-skill/main/AGENTS.mdgit clone --depth 1 https://github.com/lululu811/zettaranc-skillWrote 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/lululu811/zettaranc-skill/agents-md)<a href="https://agentmods.dev/instructions/lululu811/zettaranc-skill/agents-md"><img src="https://agentmods.dev/badge/instructions/lululu811/zettaranc-skill/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/lululu811/zettaranc-skill/agents-md"><img src="https://agentmods.dev/badge/instructions/lululu811/zettaranc-skill/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 | $0.04754 | $0.04754 |
| Opus 5 | $0.02377 | $0.02377 |
| Sonnet 5 | $0.00951 | $0.00951 |
| Haiku 4.5 | $0.00475 | $0.00475 |
Grade A, and why
zettaranc-skill 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 11d 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 — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository Guidelines
本文件面向 AI 编程 Agent：是功能指南，不是架构全书。架构细节在
docs/，模块树在源码，这里只给入口、命令、约定、关键路径与注意事项。所有事实（版本、命令、路径）均对照仓库核实。
Project Overview
zettaranc-skill = 「Z 哥（zettaranc/万千）思维框架蒸馏包」+「A 股真实数据量化工具」双轨项目。
- 核心交付物：
SKILL.md（Skill-Schema-V2 合规的角色扮演协议，被 Claude Code/Cursor 加载）——LLM 用 Z 哥角色生成点评/话术。 - 数据层：Python 包
modules/，只负责数据准备（指标、信号、回测、评分），不做投资话术——这是刻意分层，避免「AI 味」。 - 可选层：
api/（FastAPI REST）+frontend/（React 看板）+rust/（Rust 加速计算核）。 - 当前版本：
v4.2.0（pyproject.toml、SKILL.md、skill.json、docs/CHANGELOG.md顶端四处一致）。 - 许可证：MIT。
Architecture & Data Flow
双模式
| 模式 | 环境变量 | 说明 |
|---|---|---|
| JNB / 真实数据 | DATA_MODE=jnb |
走数据源取真实行情，可算指标/战法 |
| 普通小万 | DATA_MODE=websearch |
纯 LLM 对话，无事可查外部数据 |
数据源优先级（modules/datasource.py 的 CompositeDataSource）
auto 模式按 token 感知降级：
hithink（HITHINK_FINANCE_API_KEY 配置时最优先，v4.2.0）
→ Indevs（INDEVS_API_KEY，v3.8.1）
→ Tushare Pro（JNB 模式配置 TUSHARE_TOKEN）
→ a-stock-data（免费源，零配置默认，v4.1.0）
→ tushare-data-bridge（HTTP 缓存代理）
→ 本地 SQLite（data/stock_data.db，离线兜底）
约定：DB 优先读 K 线（先查 daily_kline 表，没有才调 API 并写回）。K 线读取统一走 modules/indicators/data_layer.py::get_kline_data 或 modules/strategies/core.py::get_kline_data。数据源缺 key 时绝不编造价格/信号，明确报告当前数据状态。
数据流链条
数据源 (CompositeDataSource)
→ indicators/data_layer.py # get_kline_data + indicator_cache + analyze_stock() 30步管线 → IndicatorResult
→ strategies/__init__.py # detect_all_strategies(ts_code, days) 折叠每日战法探测器 → 战法信号
→ screener/engine.py # screen_stocks(criteria, ...) 并行选股
→ backtest/ + simulator/ # 单策略/组合回测/少女少妇模拟器 → 绩效结果
→ verify/pipeline.py # 五项硬指标验收（v1.0）
→ CLI --json / Web API # 宿主消费结构化数据
Rust 加速桥（重要）
回测热路径有一层 Rust 计算核，经 PyO3 桥接进 Python：
modules/core/_rust_compat.py # ZETTARANC_BACKTEST_IMPL=rust|python|auto（默认 rust）
modules/backtest/_rust_bridge.py # is_rust_available() / try_call(name,...) → 失败业务层 fallback 到 Python
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.
- 11d ago First seen · 221 lines · 4,754 tokens per session scan A 118d25fee26c
zettaranc-skill AGENTS.md is an instructions file published in the GitHub repository lululu811/zettaranc-skill (463 stars, last pushed 8d ago), licensed MIT. It adds 4,754 tokens to every session, about $0.0238 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).
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.
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.