LangAlpha is an agent workspace for researching financial markets and supporting investment decisions through persistent research, news analysis, and parallel subagents. It is for investors who want to develop and update trading theses over time, including generating long-short pair-trade ideas. The catalogue entries provide the skills, instructions, MCP servers, and plugin that make up its agent workflow.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ginlix-ai/LangAlpha --skill idea-generationgit clone --depth 1 https://github.com/ginlix-ai/LangAlphaWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ginlix-ai/langalpha/idea-generation)<a href="https://agentmods.dev/skills/ginlix-ai/langalpha/idea-generation"><img src="https://agentmods.dev/badge/skills/ginlix-ai/langalpha/idea-generation.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00016 | $0.01143 |
| Opus 5 | $0.00008 | $0.00571 |
| Sonnet 5 | $0.00003 | $0.00229 |
| Haiku 4.5 | $0.00002 | $0.00114 |
Grade A, and why
idea-generation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Idea Generation
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".
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
Data sourcing:
- Use
screen_stockstool with filters (market cap, sector, price, volume, beta, dividend, etc.) to generate initial candidate lists - Use
get_company_overviewtool for quick company snapshot with ratios, earnings, analyst consensus - Use fundamentals MCP:
get_financial_statements(symbol)for detailed financials (income statement, balance sheet, cash flow) - Use fundamentals MCP:
get_insider_trades(symbol)for insider transactions and buy/sell stats - Use fundamentals MCP:
get_shares_float(symbol)for float data and short interest - Use fundamentals MCP:
get_technical_indicator(symbol, 'rsi'),get_technical_indicator(symbol, 'macd')for technical signals - Use
WebSearch/WebFetchfor recent news and catalysts
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)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago Changed 6b69311dc92a
- 7d ago First seen · 131 lines · 16 tokens per session scan A 709ce5ba481b
idea-generation is a skill published in the GitHub repository ginlix-ai/LangAlpha (1,724 stars, last pushed today), licensed Apache-2.0. It adds 16 tokens to every session and 1,143 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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