Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/jcstack/ashare-ai-analyst/claude-mdgit clone --depth 1 https://github.com/Jcstack/ashare-ai-analystWrote 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/jcstack/ashare-ai-analyst/claude-md)<a href="https://agentmods.dev/instructions/jcstack/ashare-ai-analyst/claude-md"><img src="https://agentmods.dev/badge/instructions/jcstack/ashare-ai-analyst/claude-md.svg" alt="Measured on agentmods" 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 | $0.00966 | $0.00966 |
| Opus 5 | $0.00483 | $0.00483 |
| Sonnet 5 | $0.00193 | $0.00193 |
| Haiku 4.5 | $0.00097 | $0.00097 |
Grade A, and why
ashare-ai-analyst 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 3d 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
Guidance for Claude Code and other AI assistants
working in this repository. For full detail, read docs/guides/development-guide.md.
Project
LLM-powered A-share (Chinese stock) market analysis & prediction platform. Personal
learning / technical-exploration toy project — outputs are not investment advice
(see the disclaimer in README.md).
Stack
Python 3.13 · FastAPI · React 19 + TypeScript · AKShare · Qlib (optional) · Celery + Redis
· SQLite · Docker Compose. LLM layer: Claude (via the Claude Code bridge or the Anthropic
API) + Google Gemini fallback — configured in config/llm.yaml.
Architecture
AI-first (v2): three signal sources → autonomous OODA agent loop → risk gates → (simulated) execution, over a Redis-Streams event bus.
src/data/ (multi-source data) → signals: src/intelligence/ + src/intelligence_hub/
(intel pipeline, knowledge graph), src/quant/ (HMM regime, alpha, signal library),
src/recommendation/ (智能选股) → src/agent_loop/ (OODA: aggregate → Bayesian prescreen
→ debate → risk gates → Kelly sizing; InvestmentDirector, ThesisTracker, calibration) →
src/risk/ + src/trading/ (circuit breaker, VaR, gates, A-share constraints — simulation only)
- Event bus
src/event_bus/(Redis Streams) · classic analysissrc/analysis/→src/prediction/→src/strategy/+src/backtest/ - Web API
src/web/(FastAPI) · Frontendfrontend/(React SPA) - LLM gateway
src/llm/(multi-provider router + Claude Code bridge) · legacy agentssrc/agents/ - Market intelligence
src/market_intelligence/,src/intelligence/ - Automation
openclaw/(Celery beat + always-on daemon) · Configconfig/*.yaml - Research workstation
research/— a separate Claude Code project root with an analyst persona (cd research && claude; seeresearch/CLAUDE.md)
Setup
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
cp .env.example .env # then fill in your API keys
cd frontend && npm install
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.
- 3d ago First seen · 82 lines · 966 tokens per session scan A 92f2e5a15a8e
ashare-ai-analyst CLAUDE.md is an instructions file published in the GitHub repository Jcstack/ashare-ai-analyst (5 stars, last pushed 2mo ago), licensed MIT. It adds 966 tokens to every session, about $0.0048 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 2026-08-31.
Other instructions, from other repositories
china-financial-services AGENTS.md
Instructions for cyijun/china-financial-services, covering agents.md, 项目边界, 目录、marketplace 与唯一数据源, 数据、安全与研究证据 and 修改原则.
aifolimizer CLAUDE.md
Instructions for tusharagg1/aifolimizer, covering aifolimizer - project context, session startup (read every new session), what this is, architecture and how to start.
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china-financial-services CLAUDE.md
Instructions for cyijun/china-financial-services, a project described as: AI agent plugins & managed-agent templates for China A-share market research and financial modeling, powered by Tushare. Research workflows and valuation tools for professional analyst review—not investment advice. | 面向中国 A 股市场的 AI…
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AGENTS.md instructions for tchivs/aktools-pro, covering agents.md - cross-agent development guide, 🤖 multi-agent compatibility protocol, 🎯 role & mission, 🏗 project architecture and 🛠 standard operating procedures (sops).
TradingAgents-astock CLAUDE.md
Claude Code instructions for simonlin1212/TradingAgents-astock, covering tradingagents-astock, 项目概述, 架构, 数据层(v0.2.5 全部直连 http,零第三方数据库依赖) and agent 角色(7 个).