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 skills/nevergoodstudy-hub/wechat-article-summarizer/alpha-vantagenpx skills add nevergoodstudy-hub/wechat-article-summarizer --skill alpha-vantagegit clone --depth 1 https://github.com/nevergoodstudy-hub/wechat-article-summarizerWrote 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/nevergoodstudy-hub/wechat-article-summarizer/alpha-vantage)<a href="https://agentmods.dev/skills/nevergoodstudy-hub/wechat-article-summarizer/alpha-vantage"><img src="https://agentmods.dev/badge/skills/nevergoodstudy-hub/wechat-article-summarizer/alpha-vantage.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 5.1 | $0.00126 | $0.01591 |
| Opus 5 | $0.00063 | $0.00796 |
| Sonnet 5 | $0.00025 | $0.00318 |
| Haiku 4.5 | $0.00013 | $0.00159 |
Grade A, and why
alpha-vantage scanned grade A with 1 finding 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 5d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.get(BASE_URL, params={"function": function, "apikey": API_KEY, **params}) This is a copy
86% identical to alpha-vantage — 3 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.
How it starts
The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Alpha Vantage — Financial Market Data
Access 20+ years of global financial data: equities, options, forex, crypto, commodities, economic indicators, and 50+ technical indicators.
API Key Setup (Required)
- Get a free key at https://www.alphavantage.co/support/#api-key (premium plans available for higher rate limits)
- Set as environment variable:
export ALPHAVANTAGE_API_KEY="your_key_here"
Installation
uv pip install requests pandas
Base URL & Request Pattern
All requests go to:
https://www.alphavantage.co/query?function=FUNCTION_NAME&apikey=YOUR_KEY&...params
import requests
import os
API_KEY = os.environ.get("ALPHAVANTAGE_API_KEY")
BASE_URL = "https://www.alphavantage.co/query"
def av_get(function, **params):
response = requests.get(BASE_URL, params={"function": function, "apikey": API_KEY, **params})
return response.json()
Quick Start Examples
# Stock quote (latest price)
quote = av_get("GLOBAL_QUOTE", symbol="AAPL")
price = quote["Global Quote"]["05. price"]
# Daily OHLCV
daily = av_get("TIME_SERIES_DAILY", symbol="AAPL", outputsize="compact")
ts = daily["Time Series (Daily)"]
# Company fundamentals
overview = av_get("OVERVIEW", symbol="AAPL")
print(overview["MarketCapitalization"], overview["PERatio"])
# Income statement
income = av_get("INCOME_STATEMENT", symbol="AAPL")
annual = income["annualReports"][0] # Most recent annual
# Crypto price
crypto = av_get("DIGITAL_CURRENCY_DAILY", symbol="BTC", market="USD")
# Economic indicator
gdp = av_get("REAL_GDP", interval="annual")
# Technical indicator
rsi = av_get("RSI", symbol="AAPL", interval="daily", time_period=14, series_type="close")
API Categories
| Category | Key Functions |
|---|---|
| Time Series (Stocks) | GLOBAL_QUOTE, TIME_SERIES_INTRADAY, TIME_SERIES_DAILY, TIME_SERIES_WEEKLY, TIME_SERIES_MONTHLY |
| Options | REALTIME_OPTIONS, HISTORICAL_OPTIONS |
| Alpha Intelligence | NEWS_SENTIMENT, EARNINGS_CALL_TRANSCRIPT, TOP_GAINERS_LOSERS, INSIDER_TRANSACTIONS, ANALYTICS_FIXED_WINDOW |
| Fundamentals | OVERVIEW, ETF_PROFILE, INCOME_STATEMENT, BALANCE_SHEET, CASH_FLOW, EARNINGS, DIVIDENDS, SPLITS |
| Forex (FX) | CURRENCY_EXCHANGE_RATE, FX_INTRADAY, FX_DAILY, FX_WEEKLY, FX_MONTHLY |
| Crypto | CURRENCY_EXCHANGE_RATE, CRYPTO_INTRADAY, DIGITAL_CURRENCY_DAILY |
| Commodities | GOLD (WTI spot), BRENT, NATURAL_GAS, COPPER, WHEAT, CORN, COFFEE, ALL_COMMODITIES |
| Economic Indicators | REAL_GDP, TREASURY_YIELD, FEDERAL_FUNDS_RATE, CPI, INFLATION, UNEMPLOYMENT, NONFARM_PAYROLL |
| Technical Indicators | SMA, EMA, MACD, RSI, BBANDS, STOCH, ADX, ATR, OBV, VWAP, and 40+ more |
What ships with it
8 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.
- 5d ago First seen · 143 lines · 126 tokens per session scan A 9510269180a7
alpha-vantage is a skill published in the GitHub repository nevergoodstudy-hub/wechat-article-summarizer (5 stars, last pushed 2mo ago), licensed MIT. It adds 126 tokens to every session and 1,591 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 86% identical to alpha-vantage, differing in 3 lines, and is treated as a copy.
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