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 leecyno1/boutique-skills --skill alphaear-stockgit clone --depth 1 https://github.com/leecyno1/boutique-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/leecyno1/boutique-skills/alphaear-stock)<a href="https://agentmods.dev/skills/leecyno1/boutique-skills/alphaear-stock"><img src="https://agentmods.dev/badge/skills/leecyno1/boutique-skills/alphaear-stock/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/leecyno1/boutique-skills/alphaear-stock"><img src="https://agentmods.dev/badge/skills/leecyno1/boutique-skills/alphaear-stock.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 | $0.00043 | $0.00395 |
| Opus 5 | $0.00022 | $0.00198 |
| Sonnet 5 | $0.00009 | $0.00079 |
| Haiku 4.5 | $0.00004 | $0.00040 |
Grade A, and why
alphaear-stock 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 11d 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.
This is a copy
100% identical to alphaear-stock — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
AlphaEar Stock Skill
Overview
Search A-Share/HK/US stock tickers and retrieve historical price data (OHLCV).
Capabilities
1. Stock Search & Data
Use scripts/stock_tools.py via StockTools.
- Search:
search_ticker(query)- Fuzzy search by code or name (e.g., "Moutai", "600519").
- Returns: List of
{code, name}.
- Get Price:
get_stock_price(ticker, start_date, end_date)- Returns DataFrame with OHLCV data.
- Dates format: "YYYY-MM-DD".
- Get Fundamentals:
get_stock_fundamentals(ticker)- Returns dict with sector, industry, market cap, PE ratio, and summary.
- Supports A-Share/HK/US stocks.
Dependencies
pandas,requests,akshare,yfinancescripts/database_manager.py(stock tables)
Notes
- Proxy: For US stock data (via
yfinance), you may need to set environment variables if your network cannot reach Yahoo Finance directly:export HTTP_PROXY="http://<proxy_ip>:<port>" export HTTPS_PROXY="http://<proxy_ip>:<port>" - A-Share/HK: Data is primarily fetched via
akshare(EastMoney), which usually works best with a direct connection in China. The tool automatically detects proxy issues and attempts direct connection for these markets.
What ships with it
4 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.
- 11d ago First seen · 41 lines · 43 tokens per session scan A c7ac3825c2c9
alphaear-stock is a skill published in the GitHub repository leecyno1/boutique-skills (5 stars, last pushed 20d ago), licensed MIT. It adds 43 tokens to every session and 395 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to alphaear-stock, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
sector-rotation
An analysis framework for comparing industries in the Chinese A-share stock market, using business conditions, price momentum, valuation, and money flows. It produces rankings and higher- or lower-allocation suggestions.
strategy-pivot-designer
Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.
twitter-reader
Read Twitter/X for financial research using opencli (read-only). Use this skill whenever the user wants to read their Twitter feed, search for financial tweets, view bookmarks, look up user profiles, or gather market sentiment from Twitter/X. Triggers include: "check my feed", "search Twitter for", "show my…
chenhao-limit-up
A framework for judging Chinese A-share stocks that have reached the daily price-rise limit, using market mood, sector leadership, and trading momentum.
trading-risk-gate
Unified pre-trade safety gate: Ruin check (Law #1), ergodicity audit, and win-rate dominance validation. Absorbs: ergodicity-check, law-of-ruin, win-rate-dominance.
furusato
A Japanese hometown-tax donation manager for furusato nozei, a system where donations to municipalities can qualify for an income-tax or local-tax deduction. It reads donation receipts, stores donation records, and calculates deduction limits.