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 sector-overviewgit 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/sector-overview)<a href="https://agentmods.dev/skills/ginlix-ai/langalpha/sector-overview"><img src="https://agentmods.dev/badge/skills/ginlix-ai/langalpha/sector-overview/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/sector-overview"><img src="https://agentmods.dev/badge/skills/ginlix-ai/langalpha/sector-overview.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 | $0.00043 | $0.01733 |
| Opus 5.5 | $0.00017 | $0.00693 |
| Sonnet 5.5 | $0.00009 | $0.00347 |
| Haiku 4.5 | $0.00004 | $0.00173 |
Grade A, and why
sector-overview 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 1mo 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
89% identical to sector-overview — 127 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sector Overview
A landscape report on an industry: how it earns money, who is winning, what it is worth, and what would change that. The quality of the report is decided in the first step, not the last: a set classified into the wrong archetype produces the right-looking report with the wrong metrics, the wrong multiple and the wrong risks.
Evidence labels, source tiers, staleness, the readiness posture and the intake limits: .agents/skills/research-conventions/SKILL.md, read before the first deliverable.
Workflow
1. Scope it
- Sector or subsector, and how narrowly the boundary is drawn.
- Purpose: a client report, a research packet, pitch material, idea generation.
- Angle: a neutral landscape, or a thematic thesis the report is testing.
- Universe: public names only, or private included.
- Depth: default
working analysis; a sector screen is afirst pass. Bands and what to cut first:.agents/skills/research-conventions/references/depth.md.
2. Classify into an archetype before analysing
Write down how each company in the set actually earns money, and put it in an archetype. Business model beats label: two names carrying the same sector tag and different revenue mechanics share no metric set, no valuation lens and no risk list. Classify from the revenue recognition note and the segment note of the largest names in the set, not from the sector tag.
Load the lens for the set before Step 3:
- Software, internet, marketplace or advertising:
.agents/skills/sector-overview/references/sectors/software-and-internet.md. - Banks, lenders and capital-markets firms:
.agents/skills/sector-overview/references/sectors/banks.md. - Producing, moving, refining or selling energy:
.agents/skills/sector-overview/references/sectors/energy.md. - Any other sector, and adding a lens for it:
.agents/skills/sector-overview/references/sectors/README.md.
Every company in the set carries one archetype label before a metric is pulled, and the comparison table in Step 4 is the archetype's metric set rather than a generic one.
What ships with it
4 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.
- 1mo ago Changed · +2 lines · +24 tokens per session d5a97973de1a
- 1mo ago First seen · 90 lines · 19 tokens per session scan A 3a0e2bd05575
sector-overview is a skill published in the GitHub repository ginlix-ai/LangAlpha (2,155 stars, last pushed today), licensed Apache-2.0. It adds 43 tokens to every session and 1,733 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to sector-overview, differing in 127 lines, and is treated as a copy.
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