A market timing state machine that detects Follow-Through Day signals to confirm market bottoms using the S&P 500 and NASDAQ indices.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install einstein-research-ftd-dv
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 einstein-research-ftd-dv 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 Follow-Through Day (FTD) Detector?
The Follow-Through Day (FTD) Detector is a specialized technical analysis tool designed to identify the definitive end of a market correction. Based on the proven William O'Neil methodology, this skill automates the detection of high-conviction rally attempts, providing traders with an offensive signal to increase equity exposure when the probability of success is highest. By integrating this capability within Openclaw Skills, developers and traders can build sophisticated market timing workflows that monitor both the S&P 500 and NASDAQ for institutional buying signals.
Follow-Through Day (FTD) Detector Use Cases
- Identifying the start of a new bull market after a correction of 10% or more.
- Confirming if a recent market bounce has the institutional volume to sustain an uptrend.
- Automating the transition from cash to equity positions based on empirical market breadth.
- Tracking dual-index signals to ensure broad market participation in a rally.
How Follow-Through Day (FTD) Detector Works
- The skill monitors market indices to identify a correction state when price makes new lows.
- It triggers a Rally Attempt (Day 1) when an index closes higher or holds above a low after a downtrend.
- A state machine begins a daily count, entering the FTD Watch phase between days 4 and 10 of the attempt.
- It evaluates if a major index closes >1.5% higher on increased volume compared to the previous day.
- Once confirmed, the skill enters a Post-FTD Monitoring phase to verify the health of the new uptrend and alert the user.
Follow-Through Day (FTD) Detector Setup
To deploy this component within your environment, ensure you have the necessary dependencies installed for data retrieval.
# Install the research suite containing the FTD skill
pip install einstein-research
# Run the FTD analysis for the latest market data
einstein-research ftd
The skill utilizes yfinance for real-time and historical data fetching and maintains a local cache to optimize performance for Openclaw Skills users.
Follow-Through Day (FTD) Detector Data Schema & Taxonomy
The skill produces a structured JSON output reflecting the current state of the market cycle:
| Field | Description |
|---|---|
| status | The global state of the market (e.g., FTD_CONFIRMED, RALLY_ATTEMPT, CORRECTION) |
| details | A natural language summary of the current market signal |
| spy / qqq | Objects containing index-specific data including day counts and price change percentages |
| ftd_date | The specific timestamp when the Follow-Through Day was validated |
| recommendation | Actionable guidance based on the current O'Neil methodology state |
Follow-Through Day (FTD) Detector Advanced Features
- Dual-index tracking for SPY and QQQ to ensure high-confidence signals via cross-index confirmation.
- Sophisticated state machine logic that distinguishes between simple bounces and institutional follow-through days.
- Local caching mechanism to reduce API calls and improve execution speed for daily automated tasks.
- Seamless integration with cron jobs for automated daily market close analysis and alerting.
SKILL.md
Loading
Related Openclaw Skills
Sora 2 Generate
A professional-grade skill for generating high-fidelity AI videos from text prompts or public image URLs using the Sora 2 engine.
Lobster Memory Master
Lobster Memory Master is a comprehensive long-term memory management system that transforms stateless AI into a stateful assistant with persistent recall and automated context compaction.
Smart Answering Framework
A sophisticated reasoning framework that dynamically adapts response structures based on question types to deliver evidence-based, natural-sounding answers.
Python Code Review
An expert AI reviewer that enforces PEP8 standards, type safety, and efficient async patterns in Python codebases.
ADA-Predictor: Biologic Therapy Risk Stratification
A clinical decision support tool that predicts the probability of developing anti-drug antibodies against biologics in rheumatic disease patients.
Feishu Image Sender
A specialized utility for sending inline images directly through the Feishu Open Platform API, bypassing standard file attachment limitations.
Featured*
