Thesis Tracker
Track and monitor investment thesis milestones, update conviction scores, and flag when thesis assumptions are being tested.
What this skill does
Track the core arguments behind every portfolio position to ensure your investment decisions remain grounded in data rather than emotion. Generate structured scorecards and conviction reports that highlight when key assumptions are being proven or disproven, then use these insights during quarterly reviews to validate, adjust, or exit positions.
Thesis Tracker
description: Maintain and update investment theses for portfolio positions and watchlist names. Track key data points, catalysts, and thesis milestones over time. Use when updating a thesis with new information, reviewing position rationale, or checking if a thesis is still intact. Triggers on “update thesis for [company]”, “is my thesis still intact”, “thesis check”, “add data point to [company]”, or “review my positions”.
Workflow
Step 1: Define or Load Thesis
If creating a new thesis:
- Company: Name and ticker
- Position: Long or Short
- Thesis statement: 1-2 sentence core thesis (e.g., “Long ACME — margin expansion from pricing power + operating leverage as mix shifts to software”)
- Key pillars: 3-5 supporting arguments
- Key risks: 3-5 risks that would invalidate the thesis
- Catalysts: Upcoming events that could prove/disprove the thesis (earnings, product launches, regulatory decisions)
- Target price / valuation: What’s it worth if the thesis plays out
- Stop-loss trigger: What would make you exit
If updating an existing thesis, ask the user for the new data point or development.
Step 2: Update Log
For each new data point or development:
- Date: When this happened
- Data point: What changed (earnings beat, management departure, competitor move, etc.)
- Thesis impact: Does this strengthen, weaken, or neutralize a specific pillar?
- Action: No change / Increase position / Trim / Exit
- Updated conviction: High / Medium / Low
Step 3: Thesis Scorecard
Maintain a running scorecard:
| Pillar | Original Expectation | Current Status | Trend |
|---|---|---|---|
| Revenue growth >20% | On track | Q3 was 22% | Stable |
| Margin expansion | Behind | Margins flat YoY | Concerning |
| New product launch | Pending | Delayed to Q2 | Watch |
Step 4: Catalyst Calendar
Track upcoming catalysts:
| Date | Event | Expected Impact | Notes |
|---|---|---|---|
Step 5: Output
Thesis summary suitable for:
- Morning meeting discussion
- Portfolio review
- Risk committee presentation
Format: Concise markdown or Word doc with the scorecard, recent updates, and current conviction level.
Important Notes
- A thesis should be falsifiable — if nothing could disprove it, it’s not a thesis
- Track disconfirming evidence as rigorously as confirming evidence
- Review theses at least quarterly, even when nothing dramatic has happened
- If the user manages multiple positions, offer to do a full portfolio thesis review
- Store thesis data in a structured format so it can be referenced across sessions
Install this Skill
Skills give your AI agent a consistent, structured approach to this task — better output than a one-off prompt.
npx skills add anthropics/financial-services-plugins --skill equity-research Official Anthropic skill. Need a walkthrough? See the install guide →
Works with
No terminal needed — Claude.ai works by pasting the skill into custom instructions.
Details
- Category
- Equity Research
- License
- Apache 2.0
- Author
- @anthropics
- Source
- GitHub →
- Source file
-
show path
equity-research/skills/thesis-tracker/SKILL.md