TickerDB provides AI agents with pre-computed, categorical market context to improve financial reasoning and significantly reduce token consumption.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install tickerdb
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install tickerdb using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is TickerDB Market Intelligence?
TickerDB is a specialized market data intelligence tool designed specifically for LLMs and AI agents within the Openclaw Skills ecosystem. Unlike traditional financial APIs that return raw OHLCV or complex indicator values, TickerDB provides derived categorical bands—such as deep_oversold or strong_uptrend—which are far more efficient for model reasoning and context windows.
By offloading complex technical and fundamental calculations to TickerDB, developers can build more accurate financial agents that consume fewer tokens while maintaining high factual reliability. This skill supports a wide range of assets including US stocks, crypto (USD pairs), and ETFs, delivering end-of-day data that is factual, unbiased, and optimized for automated workflows.
TickerDB Market Intelligence Use Cases
- Monitoring specific stock and crypto portfolios for trend reversals or extreme conditions using Openclaw Skills.
- Automating daily morning briefings on market sentiment and technical setups for customized watchlists.
- Searching for assets matching specific categorical criteria like undervalued tech stocks in a strong uptrend.
- Analyzing historical band transitions to understand aftermath performance patterns and market cycles.
- Integrating real-time market shift alerts into team communication tools via structured webhooks.
How TickerDB Market Intelligence Works
- Authenticate using your API key to securely connect your AI agent to the TickerDB engine.
- Define a persistent, server-side watchlist of tickers to enable ongoing monitoring and change detection.
- Request categorical snapshots or historical series for specific assets to feed the agent context.
- Apply complex filters via the search endpoint to discover new market opportunities based on technical or fundamental states.
- Configure webhooks or scheduled cron jobs to automate data-driven responses to significant market shifts.
TickerDB Market Intelligence Setup
To begin using this skill, you must first obtain an API key from TickerDB. You can do this via the slash command or the website.
# Login or create an account to get your key
/tickerdb login
# Configure your API key in your environment
export TICKERDB_KEY=your_api_key_here
# Alternatively, set it via the Openclaw Skills configuration
openclaw config set skills.tickerdb.apiKey your_api_key_here
TickerDB Market Intelligence Data Schema & Taxonomy
TickerDB organizes market intelligence into logical sections and categorical bands, ensuring data is structured for high-performance AI reasoning:
| Section | Key Data Points |
|---|---|
| Identity | Ticker, asset class, sector, and data freshness |
| Trend | Direction, duration, MA alignment, and volume confirmation |
| Momentum | RSI/Stochastic zones, MACD state, and divergence detection |
| Fundamentals | Valuation zones, growth direction, and analyst consensus |
| Levels | Support/Resistance status, distance bands, and test frequency |
| Volatility | Regime type, squeeze status, and historical durations |
TickerDB Market Intelligence Advanced Features
- Band stability metadata to assess the reliability, age, and volatility of a technical state.
- Cross-asset correlation parameters to analyze relationships between tickers, such as crypto movements relative to the S&P 500.
- Event-driven webhooks that push structured field-level diffs only when significant changes occur on a watchlist.
- Historical sampling modes that provide LLM-friendly date ranges for backtesting and trend analysis.
- Integrated slash commands for rapid account management, market lookups, and automated cron scheduling.
SKILL.md
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