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/.agents/skills/korean-stock-analysis/SKILL.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/skills/malda231125/tradingagents-kr/korean-stock-analysis)<a href="https://agentmods.dev/skills/malda231125/tradingagents-kr/korean-stock-analysis"><img src="https://agentmods.dev/badge/skills/malda231125/tradingagents-kr/korean-stock-analysis/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/skills/malda231125/tradingagents-kr/korean-stock-analysis"><img src="https://agentmods.dev/badge/skills/malda231125/tradingagents-kr/korean-stock-analysis.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 | $0.00120 | $0.01551 |
| Opus 5 | $0.00060 | $0.00776 |
| Sonnet 5 | $0.00024 | $0.00310 |
| Haiku 4.5 | $0.00012 | $0.00155 |
Grade A, and why
korean-stock-analysis 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 12d 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.
Korean Stock Analysis (Codex Skill)
Invoke explicitly with $korean-stock-analysis, or Codex selects it implicitly when the task matches the description (agents/openai.yaml sets allow_implicit_invocation). Repo-level AGENTS.md should point Codex here for KRX requests. Report a short plan + ETA before executing.
Layout
Installed at .agents/skills/korean-stock-analysis/ (Codex scans $REPO_ROOT/.agents/skills). Codex exposes no skill-dir variable, so invoke bundled scripts by their repo-root-relative path SKILL_DIR=.agents/skills/korean-stock-analysis (set it once per run, then use "$SKILL_DIR/scripts/…").
scripts/—analyze_kr_stock.sh <code> <date>(detached runner →main.py),analyze_kr_watchlist.sh <date> [codes…],kr_is_open.py,kr_preflight.py,kr_foreign_flow.py.references/report-format.md— the 📐 Slack/Telegram report template (single source).agents/openai.yaml— Codex presentation/policy metadata.
Fixed facts
- Repo
TradingAgents-KR; bundled shell scripts auto-detect the repo root from the project-level skill path, or honor an exported$TRADINGAGENTS_KOREA_REPOwhen the skill is copied elsewhere. The bundled scriptscdinto it themselves. Runner writesresults/<code>/<date>/complete_report.md. The data pre-flight is built intomain.py(aborts withDATA_UNAVAILABLEon empty KIS data). Ledger:국내주식.md. Full run ~20–40 min.
Language (기본 한국어 · language-driven)
Global project — all user-facing output follows TRADINGAGENTS_REPORT_LANGUAGE in the repo .env (default ko). Read it before reporting:
ko(default) → Slack/Telegram summary, checkpoint labels,국내주식.mdledger entries, and verification wording in Korean.en→ English ·ja→ Japanese ·zh→ Chinese (Simplified). Use the matching label map + example inreferences/report-format.md. The chat summary and the report share this language.- Write natively, never literally. Compose the summary directly in the target language's own financial register — do not translate the Korean/English word-for-word. Localize idioms, sentence flow, politeness level, and market terminology so a native reader finds it natural (a stiff literal translation is a failure). The templates are style references, not fill-in-the-blank strings.
main.pyalready localizescomplete_report.mdfrom the same var, so the attached report and your summary share one language. Never translate tickers / proper nouns.
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 49 lines · 120 tokens per session scan A 8e149dff9eeb
korean-stock-analysis is a skill published in the GitHub repository malda231125/TradingAgents-KR (6 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 120 tokens to every session and 1,551 once invoked, about $0.0006 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.
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