An AI-powered investment tracking assistant that systematically logs, tracks, and validates your market hypotheses using live financial data search.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install thesis-tracker
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 thesis-tracker 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 Thesis Tracker?
The Thesis Tracker is a highly effective, technical system designed to help investors organize and systematically validate their investment hypotheses. It acts as an intelligent registry for investment logic, preventing the cognitive bias of forgetting past predictions or ignoring negative indicators. By integrating with Openclaw Skills, developers and traders can build an automated, self-correcting feedback loop for portfolio decision-making.
Whether you are tracking macroeconomic shifts, sector rotations, or specific equity catalysts, this tool manages the entire lifecycle of an investment thesis. It parses unstructured natural language inputs, structures them into actionable triggers, and evaluates market realities using external search APIs to keep your investment strategies disciplined, objective, and backed by raw data.
Thesis Tracker Use Cases
- Tracking Sector Catalyst Timelines: Monitor specific sector inflection points, such as tracking real estate bottoming signals or technology adoption curves over a defined multi-quarter window.
- Investment Discipline & Anti-Bias Audit: Automatically log your explicit hypotheses before making trades, allowing you to review your predictive accuracy and avoid revisionist memory biases.
- Automated Macro Indicator Monitoring: Continuously watch for specific quantitative triggers (e.g., weekly ETF net inflows, volume indicators, or macro data releases) that confirm or invalidate your long-term market assumptions.
How Thesis Tracker Works
- Thesis Extraction & Structured Entry: When you express an investment opinion or state a hypothesis, the system parses the input to extract key metadata: Thesis Title, Core Assumptions, Positive/Negative Triggers, Time Window, and Target Assets. This is stored in a structured local JSON index.
- Knowledge Base Synchronization: The skill automatically formats the thesis details and synchronizes them into your personal knowledge base (such as IMA notes) with a standardized identifier, establishing a durable audit trail.
- Automated Verification Retrieval: During scheduled runs or manually triggered review loops, the system utilizes the
neodata-financial-searchtool to fetch real-time financial metrics, news, and market data related to the positive and negative triggers. - Status Evaluation: Based on the retrieved data, the system evaluates trigger progress and dynamically updates the thesis status among four states:
pending,partial,confirmed, ornegated. - Synthesized Reports: The skill generates a comprehensive, executive-style markdown report detailing active status overviews, key thesis details, positive/negative signal matches, and suggestions for future hypotheses.
Thesis Tracker Setup
Prerequisites
Make sure you have an active Openclaw environment set up. This skill relies on the neodata-financial-search tool to execute live data verification.
Installation
To integrate Thesis Tracker into your Openclaw Skills folder, clone or create the skill files in your working directory:
mkdir -p <working_directory>/thesis-tracker
touch <working_directory>/thesis-tracker/theses.json
Configuration
Initialize the theses.json schema with an empty array of theses to begin:
{
"theses": []
}
Configure your cron schedule to trigger the review task weekly to maintain continuous, automated tracking of your investment logic.
Thesis Tracker Data Schema & Taxonomy
The Thesis Tracker maintains structured tracking data locally in <working_directory>/thesis-tracker/theses.json.
Data Taxonomy
| Field | Type | Description | Example |
|---|---|---|---|
id |
String | Unique thesis identifier | "T001" |
title |
String | Single-sentence summary of the thesis | "2026H2 Real Estate Bottoming" |
created |
String | ISO date of creation | "2026-06-17" |
assumptions |
Array | Core logical pillars supporting the thesis | ["Policy easing", "Sales turnaround"] |
triggers_positive |
Array | Quantifiable events or indicators that confirm the thesis | ["Sales area YoY growth turns positive"] |
triggers_negative |
Array | Indicators that invalidate or cast doubt on the thesis | ["Developer defaults continue"] |
time_window |
String | Target validation timeframe | "2026Q3-Q4" |
targets |
Array | Relevant ETFs, equities, or market indexes | ["Real Estate ETF", "000002.SZ"] |
status |
String | Current state (pending, partial, confirmed, negated) |
"pending" |
checks |
Array | Log of chronological check results containing date, status, and summary | [{"date": "2026-06-17", "result": "pending", "summary": "..."}] |
Thesis Tracker Advanced Features
- External Search Agent Verification: Seamlessly integrates with semantic financial search engines to parse macro tables, corporate statements, and real-time market metrics.
- Weekly Review Cron Engine: Automatically reviews all pending theses on a configurable interval (such as a weekly cron task) to deliver proactive market insights directly to your workspace.
- Durable Knowledge Archival: Enforces clean database maintenance by limiting active theses to 15 key ideas, holding each to a 300-word limit, and archiving confirmed/negated theses after 30 days to optimize mental bandwidth and compute costs.
- IMA Notes Sync Integration: Automatically constructs structured IMA documentation formatted as
「投资论点{ID}: {标题}」to maintain an immutable, long-term personal diary of your analytical performance.
SKILL.md
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