Borrowing it
Nothing to install: this file belongs to malda231125/TradingAgents-KR. 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/malda231125/TradingAgents-KR/main/CLAUDE.mdgit clone --depth 1 https://github.com/malda231125/TradingAgents-KRWrote 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/malda231125/tradingagents-kr/claude-md)<a href="https://agentmods.dev/instructions/malda231125/tradingagents-kr/claude-md"><img src="https://agentmods.dev/badge/instructions/malda231125/tradingagents-kr/claude-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/malda231125/tradingagents-kr/claude-md"><img src="https://agentmods.dev/badge/instructions/malda231125/tradingagents-kr/claude-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 | $0.01553 | $0.01553 |
| Opus 5 | $0.00776 | $0.00776 |
| Sonnet 5 | $0.00311 | $0.00311 |
| Haiku 4.5 | $0.00155 | $0.00155 |
Grade A, and why
TradingAgents-KR 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 9d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
What this is
TradingAgents Korea is a Korea-market adaptation of TauricResearch/TradingAgents — a multi-agent LLM research workflow for KOSPI/KOSDAQ equities. It resolves Korean stock identifiers, prefetches data from Korean sources (KIS, DART, ECOS, Naver News) plus yfinance, builds compact feature packets, runs a LangGraph multi-agent debate, and emits a Markdown research report (Korean by default). It is a research/education project, not investment advice or an automated trading system.
Common commands
# Setup (editable install into a venv)
python3 -m venv .venv
.venv/bin/python -m pip install -e .
cp .env.example .env # then fill in API keys
# Run a single analysis (defaults: ticker 005930, today KST)
.venv/bin/python main.py [TICKER] [YYYY-MM-DD]
# Report saved under ./results/<ticker>/<date>/complete_report.md
# Interactive Rich CLI
.venv/bin/python -m cli.main # or `tradingagents` after install
# Telegram bot
.venv/bin/python -m cli.bot # requires TELEGRAM_BOT_TOKEN
# Tests (bare unittest — no pytest config, no conftest)
.venv/bin/python -m unittest discover -s tests # all tests
.venv/bin/python -m unittest tests.test_prefetch_cache # one module
.venv/bin/python -m unittest tests.test_cli_client.TestFactoryRouting # one case
# OpenClaw → Notion publishing helper
python .openclaw/skills/tradingagents-korea-analysis/scripts/run_analysis_to_notion.py \
--ticker 005930 --date YYYY-MM-DD --timeout 7200
Enable runtime timing traces with TRADINGAGENTS_TIMING_LOGS=1 (see tradingagents/runtime_trace.py).
Architecture
The pipeline: ticker resolution → data prefetch → feature packets → LangGraph agent workflow → Markdown/Notion report.
LLM execution — CLI-first, not API-first
The default provider is a local CLI backend, not a hosted API. tradingagents/llm_clients/factory.py routes llm_provider to a client; claude-cli and codex-cli both use CLIClient, which shells out to the claude or codex binary (see CLI_BACKEND_SPECS in cli_client.py) instead of sending an API key. anthropic/openai/google API clients also exist. Two model tiers are used everywhere: quick_think_llm and deep_think_llm. Provider/model defaults come from env vars (TRADINGAGENTS_LLM_PROVIDER, TRADINGAGENTS_QUICK_MODEL, TRADINGAGENTS_DEEP_MODEL) resolved in tradingagents/default_config.py.
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.
- 9d ago First seen · 77 lines · 1,553 tokens per session scan A dc7c1186b153
TradingAgents-KR CLAUDE.md is an instructions file published in the GitHub repository malda231125/TradingAgents-KR (6 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 1,553 tokens to every session, about $0.0078 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
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).
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.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.