zettaranc-skill: Instructions file for Codex

AGENTS.md

zettaranc-skill AGENTS.md is an instructions file for Codex, OpenCode from lululu811/zettaranc-skill. It costs 6,493 tokens per session, scanned A, original, MIT.

Repository instructions for AI coding agents working on the zettaranc-skill project. They describe the project, its two operating modes, its data sources, and important code paths.

In plain words
What is it for?
Understanding the repository layout, choosing between real market data and web-search conversation mode, and locating the Python data modules, API, frontend, and Rust code.
Why use it?
They give an agent the project context and rules it needs before making changes. They also explain which data source is used first and what happens when one is unavailable.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions Claude Code; mentions AGENTS.md.

This is lululu811/zettaranc-skill's own configuration. It tells Codex and OpenCode how to work on zettaranc-skill itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything zettaranc-skill configures →

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/lululu811/zettaranc-skill/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/lululu811/zettaranc-skill

Made for: Codex, OpenCode.

Wrote 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.

agentmods badge for zettaranc-skill AGENTS.md

README.md
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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.

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<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>
Per session 6,493 This file is loaded in full into every session.
When invoked 6,493 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.06493 $0.06493
Opus 5.5 $0.02597 $0.02597
Sonnet 5.5 $0.01299 $0.01299
Haiku 4.5 $0.00649 $0.00649

Measured 5d ago against content hash 3fd18e8defb7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 5d 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.

AGENTS.md · 266 lines

How it starts

The opening of the file, as written. The whole thing — 266 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:v4.13.1(pyproject.toml:7、SKILL.md frontmatter + 版本表、skill.json:3、README.md badge、docs/CHANGELOG.md 顶端、AGENTS.md 本行,共 7 处必须一致;改 pyproject.toml 的 version 时同步这 7 处,docs/INDEX.md 维护规则有同样的清单)。
  • 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_resolution.py 统一决议)

「环境变量 → 用哪个 provider」只有一个定义处:modules/datasource_resolution.py::resolve_provider()。读路径(CompositeDataSource)与写路径(DataSyncer)都消费它,因此两边永远选到同一个源。

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)

读路径(CompositeDataSource)在此基础上按方法链式回退;写路径(DataSyncer)取同一个首选源(单源,保留重试与退避语义)。

改优先级只改 resolve_provider() 一处。modules/data_sync/syncer.py 与 modules/datasource.py 此前各抄了一份环境变量判断且已经漂移(写路径没有 hithink 分支),zt sync 还直接钉死 tushare——在默认 websearch 模式下 tushare 无数据后端,整次同步静默同步 0 行却打印"同步完成"。v4.5.0 起统一。

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
                                    #   ↑ active_market_gate.py 注入闸门 port(TradingGate)控制开仓/强平
  → 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

Read the full file on GitHub · 266 lines

Changes

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.

  1. 5d ago Changed · +44 lines · +1,646 tokens per session 3fd18e8defb7
  2. 1mo ago Changed · +1 lines · +93 tokens per session ecab40b56d12
  3. 2mo ago First seen · 221 lines · 4,754 tokens per session scan A 118d25fee26c

Subscribe to this mod's changes

zettaranc-skill AGENTS.md is an instructions file published in the GitHub repository lululu811/zettaranc-skill (521 stars, last pushed 6d ago), licensed MIT. It adds 6,493 tokens to every session, about $0.0260 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.

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