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Historyofmarket

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gauss314
historyofmarket

History of Market (historyofmarket.com) — API publica con 88 datasets historicos de indices US desde 1871. S&P 500 (price, CAPE, EPS, drawdowns, changes, constituents), Nasdaq Composite/Nasdaq 100 (price, volatility, VXN, changes), Dow Jones, SOX/SMH, sector ETFs (XLK, XLF), Magnificent 7 y macro. Sin API key, CORS libre, CC BY 4.0.

Overview

Publishergauss314
Repositoryskills
Skill namehistoryofmarket
Stars
250
Forks
35
Bundled files
11
LicenseMIT
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 11 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by gauss314 on GitHub. Read the source before you install it.

Installation

Install the Historyofmarket AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/gauss314/skills/tree/main/skills/historyofmarket
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/gauss314/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/historyofmarket .claude/skills/historyofmarket
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Historyofmarket in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Historyofmarket on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Historyofmarket is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

History of Market

Skill para acceder a la API publica historyofmarket.com — 88 datasets pre-generados (JSON estatico) sobre la historia de los mercados financieros de EE.UU. desde 1871. Sin API key, sin autenticacion, CORS libre, licencia CC BY 4.0.

Cada dataset es un archivo JSON pre-generado (sin parametros). Cache: max-age=300 con stale-while-revalidate=3600. Soporta ETag.

🎯 Que datos cubre

CategoriaIndices / ETFsDatos disponibles
S&P 500SPXDaily desde 1928, CAPE desde 1871, EPS, drawdowns, volatilidad, VIX, constituents, changes, sectors, forward PE, ROE, driver decomp, return details
Nasdaq CompositeCOMPDaily desde 1971
Nasdaq 100NDXDaily desde 1985, constituents, annual returns, drawdowns, VXN, forward PE, driver decomp, rolling 5y, changes
QQQQQQReturn details (price + dividend + buyback)
Dow JonesDJIADaily desde 1914
Philadelphia SemiSOXDaily desde 1994, 30 constituents, SMH holdings, memory valuation, ratios SOX/SPX, ETF compare
Sector ETFsXLK, XLFPrice, annual returns, drawdowns, volatility, holdings, GICS reclassifications (2018/2023)
Mag 7AAPL/MSFT/NVDA/GOOGL/AMZN/META/TSLAEqual-weighted composite, concentration, correlation, AI valuation, AI capex, lineage
Macro—AIAE (equity allocation), NBER recessions, yield curve, forward PE by sector

⚡ Singularidades de este skill

  1. CAPE (Shiller PE) desde 1871 — el unico skill del repo con PE10 historico. references/VALUATION_METRICS.md

  2. Drawdowns con causa — cada drawdown incluye el evento que lo desencadeno y dias de recuperacion. references/DRAWDOWN_VOLATILITY.md

  3. Driver decomposition — descompone el retorno anual en rerating (cambio de PE) vs revision (cambio de EPS). references/VALUATION_METRICS.md

  4. GICS reclassification — impacto de los cambios de sector GICS 2018 y 2023 en XLK y XLF. references/SECTOR_ETFS.md

  5. Reconstitucion historica — los scripts permiten reconstruir miembros historicos de S&P 500 y Nasdaq 100 a una fecha dada.

🚀 Quick start

bash
# S&P 500 — century closes
curl https://historyofmarket.com/api/sp500/century.json

# Shiller CAPE
curl https://historyofmarket.com/api/sp500/pe.json

# Drawdowns historicos con causa
curl https://historyofmarket.com/api/sp500/drawdowns.json

# Constituyentes actuales S&P 500
curl https://historyofmarket.com/api/sp500/constituents.json

# Cambios historicos S&P 500 (adds/removes)
curl https://historyofmarket.com/api/sp500/changes.json

# Nasdaq 100 constituyentes actuales
curl https://historyofmarket.com/api/nasdaq/100.json

# Mag 7 concentracion en S&P 500
curl https://historyofmarket.com/api/mag7/concentration.json

# NBER recessions
curl https://historyofmarket.com/api/recessions.json

📁 File map

skills/historyofmarket/
├── SKILL.md
├── assets/
│   └── endpoints.json        ← snapshot de todos los 88 endpoints
├── references/
│   ├── SP500_METHODOLOGY.md  ← S&P 500: elegibilidad, earnings test, cambios
│   ├── NASDAQ_100_METHODOLOGY.md
│   ├── DRAWDOWN_VOLATILITY.md
│   ├── VALUATION_METRICS.md  ← CAPE, forward PE, driver decomp, ROE
│   ├── SECTOR_ETFS.md        ← XLK, XLF, GICS reclass, holdings
│   ├── MAGNIFICENT7.md       ← Mag 7, concentration, AI capex, lineage
│   └── BROADER_MARKET.md     ← Dow, SOX, recessions, yield curve
└── scripts/
    ├── reconstitute_sp500.py  ← reconstruir miembros S&P 500 a fecha dada
    ├── reconstitute_ndx.py    ← reconstruir miembros NDX a fecha dada
    └── sector_rotation.py     ← rotacion sectorial XLK vs XLF vs SPY

📚 Referencias

Para entender la teoria detras de los datos:

DocumentoContenido
references/SP500_METHODOLOGY.mdElegibilidad, earnings test, market cap minimo, comite de indices, historial de cambios
references/NASDAQ_100_METHODOLOGY.mdNasdaq 100 methodology, annual reconstitution, weight caps
references/DRAWDOWN_VOLATILITY.mdDrawdowns, intrayear vs year-end, volatilidad realizada, VIX/VXN
references/VALUATION_METRICS.mdShiller CAPE, forward PE, trailing PE, EPS, ROE, driver decomp
references/SECTOR_ETFS.mdSector ETFs XLK/XLF, GICS reclassification 2018/2023, holdings
references/MAGNIFICENT7.mdMag 7 composite, concentration in SPX, correlation, AI capex, lineage
references/BROADER_MARKET.mdDow Jones, SOX/SMH, NBER recessions, yield curve

🐍 Scripts

ScriptPropositoUso
scripts/reconstitute_sp500.pyReconstruir los 500 miembros del S&P 500 en una fecha historicapy scripts/reconstitute_sp500.py 2020-01-01
scripts/reconstitute_ndx.pyReconstruir los 100 miembros del Nasdaq 100 en una fecha historicapy scripts/reconstitute_ndx.py 2020-01-01
scripts/sector_rotation.pyAnalizar rotacion sectorial: rolling returns, correlacion, drawdowns sincronicospy scripts/sector_rotation.py

🌐 Entry points

EndpointDescripcion
/api/_manifest.jsonCatalogo completo de los 88 datasets
/api/profile.jsonPerfil del sitio para AI agents
/api/tools.jsonLista machine-callable de 68 tools
/llms.txtResumen LLM-friendly
/.well-known/llms.txtWell-known location
/ai.txtAI agent instructions
/sitemap.xmlSitemap completo (60+ panels × 6 locales)
/robots.txtRobots.txt

Ver assets/endpoints.json para el snapshot completo de los 88 endpoints con descripcion.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Historyofmarket AI skill do?

History of Market (historyofmarket.com) — API publica con 88 datasets historicos de indices US desde 1871. S&P 500 (price, CAPE, EPS, drawdowns, changes, constituents), Nasdaq Composite/Nasdaq 100 (price, volatility, VXN, changes), Dow Jones, SOX/SMH, sector ETFs (XLK, XLF), Magnificent 7 y macro. Sin API key, CORS libre, CC BY 4.0.

Why use Historyofmarket on TypingMind?

Because you install it once and use it with any model. Historyofmarket is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Historyofmarket in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gauss314/skills/tree/main/skills/historyofmarket. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Historyofmarket?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Historyofmarket?

As many as you like. As long as a model supports skills, you can use Historyofmarket with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Historyofmarket AI skill free?

Yes. It is published on GitHub by gauss314 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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