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fsi-er-idea-generation

Systematic stock screening and investment idea sourcing.

Skill by d-wwei

IndexedApache-2.0★ 17
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/d-wwei-fsi-er-idea-generation

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About

Systematic stock screening and investment idea sourcing. Combines quantitative screens, thematic research, and pattern recognition to surface new long and short ideas. Use when looking for new ideas, running screens, or conducting thematic sweeps. Triggers on "idea generation", "stock screen", "find ideas", "what looks interesting", "screen for", "new ideas", or "pitch me something".

Use cases: research, finance

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Secrets
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Install scripts
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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/fsi-er-idea-generation

What's inside

Skill name
fsi-er-idea-generation
Description
Systematic stock screening and investment idea sourcing. Combines quantitative screens, thematic research, and pattern recognition to surface new long and short ideas. Use when looking for new ideas, running screens, or conducting thematic sweeps. Triggers on "idea generation", "stock screen", "find ideas", "what looks interesting", "screen for", "new ideas", or "pitch me something".
License
Apache-2.0
Instructions
112 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Idea Generation


## Workflow

### Step 1: Define Search Criteria

Ask the user for parameters:
- **Direction**: Long ideas, short ideas, or both
- **Market cap**: Large, mid, small, micro
- **Sector**: Specific sector or cross-sector
- **Style**: Value, growth, quality, special situation, event-driven
- **Geography**: US, international, global
- **Theme**: Any specific thematic angle (AI, reshoring, aging demographics, etc.)

### Step 2: Quantitative Screens

Run screens based on the style:

**Value Screen**
- P/E below sector median
- EV/EBITDA below historical average
- Free cash flow yield >5%
- Price/book below 1.5x
- Insider buying in last 90 days
- Dividend yield above market average

**Growth Screen**
- Revenue growth >15% YoY
- Earnings growth >20% YoY
- Revenue acceleration (growth rate increasing)
- Expanding margins
- High return on invested capital (>15%)
- Strong net retention (>110% for SaaS)

**Quality Screen**
- Consistent revenue growth (5+ years)
- Stable or expanding margins
- ROE >15%
- Low debt/equity
- High free cash flow conversion
- Insider ownership >5%

**Short Screen**
- Declining revenue or decelerating growth
- Margin compression
- Rising receivables / inventory vs. sales
- Insider selling
- Valuation premium to peers without justification
- High short interest with deteriorating fundamentals
- Accounting red flags (auditor changes, restatements)

**Special Situation Screen**
- Recent IPOs / SPACs with lockup expirations
- Spin-offs in last 12 months
- Companies emerging from restructuring
- Activist involvement
- Management changes at underperforming companies

### Step 3: Thematic Sweep

For thematic ideas, research the theme and identify beneficiaries:

1. Define the thesis (e.g., "AI infrastructure spending accelerates through 2026")
2. Map the value chain — who benefits directly vs. indirectly?
3. Identify pure-play vs. diversified exposure
4. Assess which names are already "priced in" vs. under-appreciated
5. Look for second-order beneficiaries that the market hasn't connected to the theme

### Step 4: Idea Presentation

For each idea that passes the screen, present:

**[Company Name] — [Long/Short] — [One-Line Thesis]**

| Metric | Value | vs. Peers |
|--------|-------|-----------|
| Market cap | | |
| EV/EBITDA (NTM) | | |
| P/E (NTM) | | |
| Revenue growth | | |
| EBITDA margin | | |
| FCF yield | | |

**Thesis (3-5 bullets):**
- Why this is mispriced
- What the market is missing
- Catalyst to realize value

**Key Risks:**
- What would make this wrong

**Suggested Next Steps:**
- Build full model? Deep-dive diligence? Expert call?

### Step 5: Output

- Shortlist of 5-10 ideas with one-page summaries
- Screening criteria and methodology documented
- Comparison table across all ideas
- Prioritized list: which ideas to research first

## Important Notes

- Screens surface candidates, not conclusions — every screen output needs fundamental work
- The best ideas often come from intersections (e.g., quality company at value price due to temporary headwind)
- Avoid crowded trades — check ownership data, short interest, and how many analysts cover the name
- Contrarian ideas need a catalyst — being early without a catalyst is the same as being wrong
- Track idea hit rates over time — which screens and approaches produce the best ideas?
- Short ideas need higher conviction — timing is harder and risk is asymmetric

From d-wwei/openclaw-financial-services, Apache-2.0.

More from d-wwei/openclaw-financial-services

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Stars
17
Forks
4
Open issues
0
Last commit (this folder)
Feb 25, 2026 (8 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from d-wwei

Cite this page

fsi-er-idea-generation skill. Agent Mart. https://agentmart.dev/skills/d-wwei-fsi-er-idea-generation (last updated 2026-10-24)