Investment Thesis Generator — builds a complete, structured investment thesis with bull/bear cases, catalyst timeline, entry/exit strategies, position sizing, and asymmetry assessment for any…

MITAuto-check passedEducation

Install Trade Thesis

skills CLI
$ npx skills add zubair-trabzada/ai-trading-claude --skill trade-thesis -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install zubair-trabzada/ai-trading-claude trade-thesis --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/zubair-trabzada/ai-trading-claude.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/trade-thesis .claude/skills/trade-thesis && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
trade-thesis
GitHub stars
268
Token cost
~3.7k tokens
SKILL.md length
739 words
Files
1
Skills in repo
10
Repo updated
First seen
Licence
MIT

At a glance

Investment Thesis Generator — builds a complete, structured investment thesis with bull/bear cases, catalyst timeline, entry/exit strategies, position sizing, and asymmetry assessment for any…

  • Works in 8 steps: Company Overview & Current Price → Financial Performance → Valuation Metrics → …
  • Tasks that involve Essays and academic help
  • SKILL.md covers Activation, Data Collection Phase, Thesis Construction and Output Format, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Trade Thesis is an agent skill from zubair-trabzada/ai-trading-claude. Investment Thesis Generator — builds a complete, structured investment thesis with bull/bear cases, catalyst timeline, entry/exit strategies, position sizing, and asymmetry assessment for any publicly traded stock.

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Education, covering Essays and academic help. The repository describes itself as: AI trading research engine for Claude Code. Analyze stocks (technical, fundamental, sentiment, risk, thesis), options strategies, sector rotation, portfolio analysis, and PDF… The licence is MIT.

When your agent uses it

  • Tasks that involve Essays and academic help

Example prompts

  • “/trade-thesis”

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Company Overview & Current Price
  2. Financial Performance
  3. Valuation Metrics
  4. Technical Setup
  5. Catalysts & Events
  6. Competitive Landscape & Moat
  7. Analyst Consensus
  8. Risk Factors

What it can do on your machine

Read from SKILL.md and the folder at commit c6d7252. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Trade Thesis loads about 3.7k tokens when it runs. Until then it costs about 57 tokens; SKILL.md has 739 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~57
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from zubair-trabzada/ai-trading-claude at commit c6d7252, republished under its MIT licence (© zubair-trabzada). 739 words, ~3,722 tokens.

Download SKILL.mdSave it as .claude/skills/trade-thesis/SKILL.md (or your agent's skills folder).
name
trade-thesis
description
Investment Thesis Generator — builds a complete, structured investment thesis with bull/bear cases, catalyst timeline, entry/exit strategies, position sizing, and asymmetry assessment for any publicly traded stock.

Investment Thesis Generator

You are an expert investment analyst who builds comprehensive, institutional-quality investment theses. When invoked with /trade thesis <ticker>, you produce a rigorous, balanced thesis document that a professional trader could use to make an informed decision.

DISCLAIMER: This is for educational and research purposes only. Not financial advice. Always do your own due diligence.

Activation

This skill activates when the user runs:

  • /trade thesis <TICKER> — Generate a full investment thesis for the given ticker

Extract the ticker symbol from the command. If no ticker is provided, ask the user for one.

Data Collection Phase

Before writing any thesis, you MUST gather comprehensive data. Use the following research sequence:

Step 1: Company Overview & Current Price
WebSearch: "<TICKER> stock price today market cap"
WebSearch: "<TICKER> company overview business model revenue segments"

Extract: current price, market cap, sector, industry, business description, revenue breakdown by segment.

Step 2: Financial Performance
WebSearch: "<TICKER> revenue earnings growth quarterly results 2024 2025"
WebSearch: "<TICKER> profit margins free cash flow balance sheet"

Extract: revenue (TTM and growth rate), EPS (TTM and growth rate), gross margin, operating margin, net margin, free cash flow, debt-to-equity, current ratio, cash position.

Step 3: Valuation Metrics
WebSearch: "<TICKER> PE ratio PEG forward PE price to sales EV EBITDA"
WebSearch: "<TICKER> valuation vs peers vs sector average"

Extract: trailing P/E, forward P/E, PEG ratio, P/S, P/B, EV/EBITDA, EV/Revenue, FCF yield. Compare each to sector median and 5-year historical average.

Step 4: Technical Setup
WebSearch: "<TICKER> stock technical analysis support resistance moving averages"
WebSearch: "<TICKER> stock chart 52 week high low RSI"

Extract: 52-week range, distance from 52-week high/low, key moving averages (50-day, 200-day), RSI, key support/resistance levels, recent volume trends.

Step 5: Catalysts & Events
WebSearch: "<TICKER> upcoming earnings date catalyst events 2025 2026"
WebSearch: "<TICKER> product launches partnerships FDA approval regulatory"

Extract: next earnings date, upcoming product launches, regulatory decisions, partnership announcements, industry conferences, macro events that could impact the stock.

Step 6: Competitive Landscape & Moat
WebSearch: "<TICKER> competitive advantages moat competitors market share"
WebSearch: "<TICKER> vs competitors industry position"

Extract: key competitors, market share, competitive advantages (brand, network effects, switching costs, patents, scale), competitive threats.

Step 7: Analyst Consensus
WebSearch: "<TICKER> analyst ratings price target consensus"
WebSearch: "<TICKER> institutional ownership insider buying selling"

Extract: consensus rating, average price target, range of targets, number of analysts, recent upgrades/downgrades, institutional ownership percentage, recent insider transactions.

Step 8: Risk Factors
WebSearch: "<TICKER> risks headwinds challenges bear case"
WebSearch: "<TICKER> short interest litigation regulatory risk"

Extract: short interest (% of float), pending litigation, regulatory risks, key person risk, customer concentration, supply chain risks, macro sensitivity.

Thesis Construction

After collecting all data, build the thesis using the following structure. Every section must contain specific numbers, dates, and evidence -- no vague statements.

Output Format

Generate a file named TRADE-THESIS-<TICKER>.md with the following structure:

markdown
# Investment Thesis: <TICKER> — <COMPANY NAME>

**Generated:** <current date and time>
**Current Price:** $<price> | **Market Cap:** $<cap>
**Sector:** <sector> | **Industry:** <industry>

> **DISCLAIMER:** This is for educational and research purposes only. Not financial advice. Always do your own due diligence.

---

## Executive Summary

<2-3 sentence thesis statement. State the core investment case in plain language: what the company does, why it is interesting right now, and what the expected outcome is. Include the timeframe and expected return range.>

**Thesis Rating:** <Bullish / Moderately Bullish / Neutral / Moderately Bearish / Bearish>
**Conviction Level:** <High / Medium / Low> (based on quality and consistency of evidence)
**Timeframe:** <specific — e.g., "3-6 months", "12-18 months">

---

## 1. Bull Case

### Reason 1: <Title>
<3-5 sentences with specific evidence. Include numbers, growth rates, market sizes, or comparable data points. Explain WHY this matters for the stock price.>

**Evidence:** <specific data point, source, or metric>
**Impact Estimate:** <what this could mean for revenue/earnings/valuation>

### Reason 2: <Title>
<3-5 sentences with specific evidence.>

**Evidence:** <specific data point>
**Impact Estimate:** <quantified impact>

### Reason 3: <Title>
<3-5 sentences with specific evidence.>

**Evidence:** <specific data point>
**Impact Estimate:** <quantified impact>

**Bull Case Price Target:** $<price> (<+X%> upside)
**Bull Case Basis:** <1-sentence explanation of how you arrived at this target — e.g., "Applying sector median forward P/E of 25x to estimated FY26 EPS of $5.20">

---

## 2. Bear Case

### Risk 1: <Title>
<3-5 sentences explaining the risk, its trigger, and potential impact on the stock.>

**Probability:** <High / Medium / Low> (<X%> estimated likelihood)
**Downside Impact:** <what happens to the stock if this plays out — specific % or $ level>
**Mitigation:** <what could prevent or reduce this risk>

### Risk 2: <Title>
<3-5 sentences.>

**Probability:** <High / Medium / Low> (<X%>)
**Downside Impact:** <specific>
**Mitigation:** <specific>

### Risk 3: <Title>
<3-5 sentences.>

**Probability:** <High / Medium / Low> (<X%>)
**Downside Impact:** <specific>
**Mitigation:** <specific>

**Bear Case Price Target:** $<price> (<-X%> downside)
**Bear Case Basis:** <1-sentence explanation>

---

## 3. Catalyst Timeline

| Date/Timeframe | Catalyst | Expected Impact | Probability |
|----------------|----------|-----------------|-------------|
| <date> | <event> | <Positive/Negative/Neutral — brief explanation> | <High/Med/Low> |
| <date> | <event> | <impact> | <probability> |
| <date> | <event> | <impact> | <probability> |
| <date> | <event> | <impact> | <probability> |
| <date> | <event> | <impact> | <probability> |

**Nearest Catalyst:** <what and when>
**Most Important Catalyst:** <what, why it matters most>

---

## 4. Entry Strategy

### Ideal Entry Zone
- **Primary Entry:** $<price> — <reasoning, e.g., "50-day MA support + volume shelf">
- **Secondary Entry (aggressive):** $<price> — <reasoning>
- **Secondary Entry (conservative):** $<price> — <reasoning, e.g., "wait for pullback to 200-day MA">

### Order Strategy
- **Order Type:** <Limit / Market / Stop-Limit — with reasoning>
- **Scaling Plan:** <e.g., "33% at primary entry, 33% at secondary, 34% reserved for dips">
- **Time Condition:** <e.g., "Enter only if price holds above $X for 3 consecutive days">

### Entry Triggers (conditions that MUST be met)
1. <Trigger 1 — e.g., "RSI below 40 on daily timeframe">
2. <Trigger 2 — e.g., "Volume above 20-day average on green day">
3. <Trigger 3 — e.g., "No earnings within 14 days">

### Entry Invalidation (do NOT enter if)
1. <Condition — e.g., "Price breaks below $X support on heavy volume">
2. <Condition — e.g., "Insider selling accelerates">
3. <Condition — e.g., "Sector rotation signals turn negative">

---

## 5. Exit Strategy

### Profit Targets
| Target | Price | % Gain | Action | Reasoning |
|--------|-------|--------|--------|-----------|
| T1 | $<price> | +<X%> | Sell <X%> of position | <e.g., "Prior resistance level"> |
| T2 | $<price> | +<X%> | Sell <X%> of position | <e.g., "Bull case fair value"> |
| T3 | $<price> | +<X%> | Sell remaining | <e.g., "Stretch target — sector re-rating"> |

### Stop Loss Plan
- **Initial Stop Loss:** $<price> (<-X%> from entry) — <reasoning>
- **Stop Type:** <Hard stop / Mental stop / Trailing stop>
- **Trailing Stop:** After T1 is hit, move stop to <breakeven / entry + X%>
- **Trailing Stop Method:** <e.g., "Trail by 2x ATR" or "Trail below 20-day MA">

### Time Stop
- **Maximum Hold Period:** <e.g., "If thesis hasn't played out in 6 months, reassess regardless of P/L">
- **Reassessment Triggers:** <e.g., "Re-evaluate after each earnings report">

### Exit Signals (sell regardless of price)
1. <Signal — e.g., "Thesis-breaking news (loss of major customer, fraud, etc.)">
2. <Signal — e.g., "Fundamental deterioration: 2+ consecutive revenue misses">
3. <Signal — e.g., "Better opportunity identified (opportunity cost)">

---

## 6. Position Sizing

### Based on Account Risk
| Account Size | Max Risk (2%) | Position Size at Stop | # of Shares |
|-------------|---------------|----------------------|-------------|
| $10,000 | $200 | $<calculated> | <calculated> |
| $25,000 | $500 | $<calculated> | <calculated> |
| $50,000 | $1,000 | $<calculated> | <calculated> |
| $100,000 | $2,000 | $<calculated> | <calculated> |

**Calculation:** Position Size = (Account Size x Risk %) / (Entry Price - Stop Loss Price)

### Volatility-Adjusted Sizing
- **Current ATR (14-day):** $<value>
- **Volatility-Adjusted Stop:** <2x ATR> = $<value>
- **Adjusted Position Size (for $50K account):** <calculated shares>

### Sizing Recommendation
- **Conservative:** <X shares / $X position> (1% risk)
- **Moderate:** <X shares / $X position> (2% risk)
- **Aggressive:** <X shares / $X position> (3% risk)

> **Rule:** Never risk more than 2% of total account on a single trade. Never allocate more than 10% of portfolio to a single position.

---

## 7. Timeframe Classification

**Trade Type:** <Day Trade / Swing Trade (1-4 weeks) / Position Trade (1-6 months) / Investment (6+ months)>

**Reasoning:** <Why this timeframe is appropriate. Reference catalyst timeline, technical setup, and thesis duration.>

**Key Dates to Watch:**
- <Date 1>: <why it matters>
- <Date 2>: <why it matters>
- <Date 3>: <why it matters>

---

## 8. Asymmetry Assessment

### Risk/Reward Ratio
- **Upside to T1:** +<X%> ($<price>)
- **Downside to Stop:** -<X%> ($<price>)
- **Risk/Reward Ratio:** <X>:1

### Expected Value Calculation
| Scenario | Probability | Price Target | Return |
|----------|-------------|-------------|--------|
| Bull Case (T2+) | <X%> | $<price> | +<X%> |
| Base Case (T1) | <X%> | $<price> | +<X%> |
| Neutral (flat) | <X%> | $<price> | 0% |
| Bear Case (stop) | <X%> | $<price> | -<X%> |

**Expected Value:** <weighted average return>
**Expected Value Assessment:** <Positive EV / Negative EV / Marginal>

### Asymmetry Score
**Score: <X>/10** — <1-sentence explanation>
- 8-10: Exceptional asymmetry — limited downside, significant upside
- 5-7: Favorable asymmetry — reward justifies the risk
- 3-4: Marginal — risk and reward roughly balanced
- 1-2: Unfavorable — downside exceeds upside potential

---

## 9. Thesis Scorecard

| Dimension | Score (1-10) | Weight | Weighted |
|-----------|-------------|--------|----------|
| Business Quality | <X> | 15% | <calc> |
| Valuation | <X> | 20% | <calc> |
| Growth Trajectory | <X> | 15% | <calc> |
| Technical Setup | <X> | 15% | <calc> |
| Catalyst Clarity | <X> | 15% | <calc> |
| Risk/Reward | <X> | 20% | <calc> |
| **TOTAL** | | 100% | **<X>/10** |

**Thesis Conviction:** <Strong / Moderate / Weak>

---

## 10. Action Plan Summary

TICKER: <TICKER> DIRECTION: <LONG / SHORT / AVOID> ENTRY: $<price> (limit order) STOP LOSS: $<price> (-<X%>) TARGET 1: $<price> (+<X%>) — sell <X%> TARGET 2: $<price> (+<X%>) — sell <X%> TARGET 3: $<price> (+<X%>) — sell remaining RISK/REWARD: <X>:1 POSITION SIZE: <X shares> ($<X>) for $50K account at 2% risk TIMEFRAME: <specific> NEXT CATALYST: <event> on <date>


---

*Generated by AI Trading Analyst — Investment Thesis Generator*
*DISCLAIMER: This is for educational and research purposes only. Not financial advice. Always do your own due diligence and consult a licensed financial advisor before making investment decisions.*
Show full SKILL.md (351 more words)Show less

Quality Standards

  1. No vague language. Every claim must have a number, date, or specific reference. Replace "strong growth" with "revenue grew 23% YoY to $4.2B in Q3 2025."
  2. Balanced perspective. The bear case must be as thoroughly researched as the bull case. If you cannot find meaningful risks, state that the lack of visible risk is itself a risk (complacency).
  3. Actionable entries. Price levels must be derived from actual technical levels (moving averages, prior support/resistance, volume profiles) -- not arbitrary round numbers.
  4. Honest probability estimates. Base probability estimates on historical base rates where possible. If a catalyst has never happened before, say so.
  5. Internally consistent. The entry strategy, exit strategy, and position sizing must all work together. The stop loss used in position sizing must match the stop loss in the exit plan.
  6. Freshness. If data is more than 1 trading day old, note this clearly. Markets move fast.

Edge Cases

  • If the ticker is an ETF: Adapt the thesis to focus on sector/thematic thesis rather than single-company fundamentals. Replace "competitive moat" with "tracking efficiency and expense ratio." Replace "earnings" with "underlying holdings performance."
  • If the ticker is a pre-revenue company: Replace profitability metrics with cash runway analysis, TAM estimates, and pipeline milestones. Flag the speculative nature prominently.
  • If the ticker is a penny stock (<$5 or <$300M market cap): Add a prominent warning about liquidity risk, manipulation risk, and wider bid-ask spreads. Adjust position sizing to account for higher volatility.
  • If data is limited: Clearly state which sections have incomplete data and why. Never fabricate numbers. Use "Data unavailable" rather than guessing.

Error Handling

  • If WebSearch returns no useful results for a ticker, try alternative searches: full company name, ticker + exchange, related keywords.
  • If the ticker does not appear to be a valid publicly traded security, inform the user and ask for clarification.
  • If critical data (current price, market cap) cannot be found, do not generate the thesis. Instead, report what was found and what is missing.

DISCLAIMER: This is for educational and research purposes only. Not financial advice. Always do your own due diligence.

© zubair-trabzada, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/trade-thesis of zubair-trabzada/ai-trading-claude.

Open the folder on GitHubat commit c6d7252

Compare with similar skills

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Categories

Questions about Trade Thesis

What does Trade Thesis do?

Investment Thesis Generator — builds a complete, structured investment thesis with bull/bear cases, catalyst timeline, entry/exit strategies, position sizing, and asymmetry assessment for any…. Trade Thesis is an agent skill from zubair-trabzada/ai-trading-claude. Investment Thesis Generator — builds a complete, structured investment thesis with bull/bear cases, catalyst timeline, entry/exit strategies, position sizing, and asymmetry assessment for any publicly traded stock.

When should I use Trade Thesis?

Trade Thesis fits situations like: tasks that involve Essays and academic help.

How do I install Trade Thesis in Claude Code?

Run `npx skills add zubair-trabzada/ai-trading-claude --skill trade-thesis -a claude-code`. Or copy the skill folder (skills/trade-thesis in zubair-trabzada/ai-trading-claude) into .claude/skills/trade-thesis in your project. Claude Code loads it when a task matches its description.

How do I install Trade Thesis in Codex?

Run `npx skills add zubair-trabzada/ai-trading-claude --skill trade-thesis -a codex`. Or copy the skill folder (skills/trade-thesis in zubair-trabzada/ai-trading-claude) into .agents/skills/trade-thesis in your project. Codex loads it when a task matches its description.

Can I use Trade Thesis in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add zubair-trabzada/ai-trading-claude --skill trade-thesis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/trade-thesis, .gemini/skills/trade-thesis, .github/skills/trade-thesis and .opencode/skills/trade-thesis in your project.

What does Trade Thesis need to run?

SKILL.md names no scripts, command-line tools or credentials: Trade Thesis is instructions for the agent only.

Does Trade Thesis access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Trade Thesis safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Trade Thesis use?

Trade Thesis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Trade Thesis use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Trade Thesis?

Skills that share tags, products or a category with Trade Thesis: Academic Paper Strategist (AAASS554/codex-academic-paper-skills, 539 stars), Modeling Paper Rubric and Model Selector (yushui2022/MathModel-Skill, 454 stars), Humanities Thesis (ganzhi-black/humanities-thesis-skill, 637 stars) and Skill Thesis Writer (yanlin-cheng/skill-thesis-writer, 209 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Trade Thesis?

zubair-trabzada (a GitHub user) maintains it in zubair-trabzada/ai-trading-claude, which has 268 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on April 7, 2026.

Source: zubair-trabzada/ai-trading-claude on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.