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 pinkpixel-dev/skills-collection-1 --skill alpha-vantagegit clone --depth 1 https://github.com/pinkpixel-dev/skills-collection-1Wrote 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/pinkpixel-dev/skills-collection-1/alpha-vantage)<a href="https://agentmods.dev/skills/pinkpixel-dev/skills-collection-1/alpha-vantage"><img src="https://agentmods.dev/badge/skills/pinkpixel-dev/skills-collection-1/alpha-vantage/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/pinkpixel-dev/skills-collection-1/alpha-vantage"><img src="https://agentmods.dev/badge/skills/pinkpixel-dev/skills-collection-1/alpha-vantage.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 | $0.00034 | $0.01303 |
| Opus 5.5 | $0.00014 | $0.00521 |
| Sonnet 5.5 | $0.00007 | $0.00261 |
| Haiku 4.5 | $0.00003 | $0.00130 |
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 1mo 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
95% identical to alpha-vantage — 55 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 — 135 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 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.
- 1mo ago First seen · 135 lines · 34 tokens per session scan A dcfc038f77ec
alpha-vantage is a skill published in the GitHub repository pinkpixel-dev/skills-collection-1 (9 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 34 tokens to every session and 1,303 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). It is 95% identical to alpha-vantage, differing in 55 lines, and is treated as a copy.
Other skills, from other repositories
cost-efficiency-analyzer
Analyzes cost structure, cost efficiency, and expense management from P&L data. Use when the user asks about costs, expenses, COGS, operating expenses, cost ratios, cost control, spending efficiency, margin compression from cost side, or wants to understand where money is going. Also use for "are we spending too…
grocery-prices
A skill to calculate grocery prices with country-specific taxes.
prompt-proximity-architecture
Turn an approved measurement charter, ICPs, and buyer jobs into a budget-aware prompt coverage blueprint across proximity bands, aided status, information acts, journey states, roles, locales, evidence grades, partitions, and measurement lanes. Use before prompt wording to define required, optional, and prohibited…
price-alert
Fire when the tracked token does something - new ATH, sharp 1h move, or operator-set target crossed. Silent on normal days.
token-pick
One token recommendation and one prediction market pick - scored, quantified, with a skip branch when signals are weak.
unlock-monitor
Token unlock and vesting tracker - quantify supply pressure via absorption ratio, classify cliff vs linear, and deliver one-line market reads.