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 company-profilegit 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/company-profile)<a href="https://agentmods.dev/skills/ginlix-ai/langalpha/company-profile"><img src="https://agentmods.dev/badge/skills/ginlix-ai/langalpha/company-profile/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ginlix-ai/langalpha/company-profile"><img src="https://agentmods.dev/badge/skills/ginlix-ai/langalpha/company-profile.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00068 | $0.06434 |
| Opus 5.5 | $0.00027 | $0.02574 |
| Sonnet 5.5 | $0.00014 | $0.01287 |
| Haiku 4.5 | $0.00007 | $0.00643 |
Grade A, and why
company-profile 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 24d 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 — 295 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Company Profile
A single slide that answers "what is this company" for a reader with thirty seconds. Four quadrants, all four full: overview, financial summary, share price or valuation chart, key facts. This is the front page of a pitch book and the first page of a diligence pack, and it is the one slide in a deck allowed to be a document, because nobody presents from it, they read it off the page.
Build it with the pptx skill. Its geometry, palette, build-script discipline and verification scripts all apply unchanged, and this file only describes what goes inside that frame. Reach for html-report instead when the answer wants two pages of prose, and comps-analysis when the question is how the company prices against its peers rather than what it is.
Evidence labels, source tiers, staleness, the readiness posture and the intake limits: .agents/skills/research-conventions/SKILL.md, read before the first deliverable.
Scope
The profile is a baseline: what is true about this company, sourced, on one page. It is not a recommendation, and it holds no view. The moment the work turns into a thesis, a scenario set, a valuation argument or a call on the stock, it has stopped being a profile: finish the baseline, then hand off and say so. .agents/skills/initiating-coverage/SKILL.md owns the thesis, .agents/skills/comps-analysis/SKILL.md owns relative valuation, .agents/skills/earnings-preview/SKILL.md owns the setup into a print. Expanding the slide to carry a view is the failure this rule exists to catch, because a one-pager that argues reads as fact to everyone downstream of it.
Workflow
1. Scope it before researching
Confirm the entity first, then ask what the slide is for.
Entity identity. Establish, before any pull: the exact issuer (a similarly named parent, subsidiary or unrelated company is the classic wrong answer), the listing line (ticker and exchange, and which share class where more than one trades), and the fiscal year end. Everything downstream carries this, and a profile of the wrong listing line is wrong in every quadrant at once.
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.
- 24d ago Changed fe53d2842c4c
- 1mo ago First seen · 295 lines · 68 tokens per session scan A ae70b23c5448
company-profile is a skill published in the GitHub repository ginlix-ai/LangAlpha (1,817 stars, last pushed today), licensed Apache-2.0. It adds 68 tokens to every session and 6,434 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-16.
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