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 skills add ZICXR/A-Stock-Skills --skill 00-start-heregit clone --depth 1 https://github.com/ZICXR/A-Stock-SkillsWrote 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/zicxr/a-stock-skills/00-start-here)<a href="https://agentmods.dev/skills/zicxr/a-stock-skills/00-start-here"><img src="https://agentmods.dev/badge/skills/zicxr/a-stock-skills/00-start-here/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/zicxr/a-stock-skills/00-start-here"><img src="https://agentmods.dev/badge/skills/zicxr/a-stock-skills/00-start-here.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 | $0.00065 | $0.00837 |
| Opus 5 | $0.00032 | $0.00418 |
| Sonnet 5 | $0.00013 | $0.00167 |
| Haiku 4.5 | $0.00006 | $0.00084 |
Grade A, and why
start-here 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.
What it actually says
🚀 start-here: 30 秒上手
A-Stock-Skills 只有 10 个 Skill
| # | Skill | 解决什么问题 |
|---|---|---|
| 1 | astock-data-source | 拿实时行情 / K 线 (多源 fallback) |
| 2 | astock-cache | K 线 parquet 缓存 (5 秒 vs 30 分钟) |
| 3 | astock-utils | 代码转换 / 交易日历 / 工具函数 |
| 4 | watchlist-monitor | 监控自选股 + 涨跌幅告警 |
| 5 | screener | 全市场筛选 (PE / 涨幅 / MACD 等) |
| 6 | stock-technical-analysis | MA / MACD / KDJ / RSI / BOLL |
| 7 | report | 每日复盘 + 个股研报 |
| 8 | alerter | 钉钉 / 微信 / 飞书 推送 |
| 9 | trade-journal | 🆕 AI 建议 vs 实盘 复盘 |
| 10 | start-here | 🆕 本文档 |
🎯 5 个真实场景
场景 1: 拿一只股票的行情
python skills/01-infra/astock-data-source/main.py get-realtime --code 601991
场景 2: 拿 60 日 K 线 + 算 MACD
from skills.Stock_Analysis.stock_technical_analysis.main import calc_macd
from skills.Stock_Infrastructure.astock_data_source.main import get_kline
df = get_kline("601991", days=60)
macd = calc_macd(df)
print(macd.tail())
场景 3: 全市场筛选 PE<20 + 涨幅>5%
python skills/05-quant/screener/main.py screen --pe-max 20 --pct-change-min 5
场景 4: 监控自选股
# 1. 生成配置模板
python skills/02-data-collection/watchlist-monitor/main.py init
# 2. 编辑 watchlist.yaml
# 3. 启动监控
python skills/02-data-collection/watchlist-monitor/main.py monitor
场景 5: 复盘 AI 准不准
# 1. 记录今天的 AI 建议
python skills/02-data-collection/trade-journal/main.py record --code 601991 --signal "MACD金叉" --target_price 3.50
# 2. 30 天后比对
python skills/02-data-collection/trade-journal/main.py review
⚠️ 3 件必读
- 数据源问题: 住宅 IP 跑东财会被封, astock-data-source v2.0 已自动 fallback
- 缓存很重要: 第一次跑慢, 第二次快 100 倍 (用 astock-cache)
- AI 不可信, 除非复盘: 用 trade-journal 记录, 30 天后看胜率
🛡️ 免责声明
本项目所有数据来源于公开市场数据, 仅供学习研究使用, 不构成任何投资建议。投资有风险, 入市需谨慎。
What ships with it
2 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 · 79 lines · 65 tokens per session scan A cf211a90a6d1
start-here is a skill published in the GitHub repository ZICXR/A-Stock-Skills (25 stars, last pushed 2mo ago), licensed MIT. It adds 65 tokens to every session and 837 once invoked, about $0.0003 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.
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investment-research
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industry-research
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investment-checklist
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management-deep-dive
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