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 agentmods add skills/ginlix-ai/langalpha/3-statementsnpx skills add ginlix-ai/LangAlpha --skill 3-statementsgit 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/3-statements)<a href="https://agentmods.dev/skills/ginlix-ai/langalpha/3-statements"><img src="https://agentmods.dev/badge/skills/ginlix-ai/langalpha/3-statements.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 | $0.00022 | $0.03775 |
| Opus 5 | $0.00011 | $0.01887 |
| Sonnet 5 | $0.00004 | $0.00755 |
| Haiku 4.5 | $0.00002 | $0.00378 |
Grade A, and why
3-statements 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 6d 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.
This is a copy
78% identical to 3-statement-model — 70 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 370 lines — stays where its author put it; the contents beside it link to each section on GitHub.
3-Statement Financial Model Template Completion
Complete and populate integrated financial model templates with proper linkages between Income Statement, Balance Sheet, and Cash Flow Statement.
Model Structure
Identifying Template Tab Organization
Templates vary in their tab naming conventions and organization. Before populating, review all tabs to understand the template's structure. Below are common tab names and their typical contents:
| Common Tab Names | Contents to Look For |
|---|---|
| IS, P&L, Income Statement | Income Statement |
| BS, Balance Sheet | Balance Sheet |
| CF, CFS, Cash Flow | Cash Flow Statement |
| WC, Working Capital | Working Capital Schedule |
| DA, D&A, Depreciation, PP&E | Depreciation & Amortization Schedule |
| Debt, Debt Schedule | Debt Schedule |
| NOL, Tax, DTA | Net Operating Loss Schedule |
| Assumptions, Inputs, Drivers | Driver assumptions and inputs |
| Checks, Audit, Validation | Error-checking dashboard |
Template Review Checklist
- Identify which tabs exist in the template (not all templates include every schedule)
- Note any template-specific tabs not listed above
- Understand tab dependencies (e.g., which schedules feed into the main statements)
- Locate input cells vs. formula cells on each tab
Understanding Template Structure
Before populating a template, familiarize yourself with its existing layout to ensure data is entered in the correct locations and formulas remain intact.
Identifying Row Structure
- Locate the model title at top of each tab
- Identify section headers and their visual separation
- Find the units row indicating $ millions, %, x, etc.
- Note column headers distinguishing Actuals vs. Estimates periods
- Confirm period labels (e.g., FY2024A, FY2025E)
- Identify input cells vs. formula cells (typically distinguished by font color)
Identifying Column Structure
- Confirm line item labels in leftmost column
- Verify historical years precede projection years
- Note the visual border separating historical from projected periods
- Check for consistent column order across all tabs
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 6d ago First seen · 370 lines · 22 tokens per session scan A 1b69eb8bbb74
3-statements is a skill published in the GitHub repository ginlix-ai/LangAlpha (1,724 stars, last pushed today), licensed Apache-2.0. It adds 22 tokens to every session and 3,775 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 78% identical to 3-statement-model, differing in 70 lines, and is treated as a copy.
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