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 earnings-analysisgit 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/earnings-analysis)<a href="https://agentmods.dev/skills/ginlix-ai/langalpha/earnings-analysis"><img src="https://agentmods.dev/badge/skills/ginlix-ai/langalpha/earnings-analysis/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/earnings-analysis"><img src="https://agentmods.dev/badge/skills/ginlix-ai/langalpha/earnings-analysis.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 | $0.00076 | $0.01791 |
| Opus 5.5 | $0.00030 | $0.00716 |
| Sonnet 5.5 | $0.00015 | $0.00358 |
| Haiku 4.5 | $0.00008 | $0.00179 |
Grade A, and why
earnings-analysis 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
94% identical to earnings-analysis — 246 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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Earnings Update
A post-print report on a company already under coverage: what changed this quarter, whether the change recurs, what it does to estimates, and what it does to the thesis. Eight to twelve pages of DOCX, inside 48 hours of the release, written for a reader who already knows the company.
Route elsewhere when the request is a first-time initiation (.agents/skills/initiating-coverage/SKILL.md), a pre-print setup (.agents/skills/earnings-preview/SKILL.md), or a same-morning reaction blurb (.agents/skills/morning-note/SKILL.md).
Evidence labels, source tiers, staleness, the readiness posture and the intake limits: .agents/skills/research-conventions/SKILL.md, read before the first deliverable.
Output modes
| Mode | Fires when | Contract |
|---|---|---|
| Deep dive | the default | every phase present, the length budget below, assembled as a DOCX through .agents/skills/docx/SKILL.md |
| One-pager | the user asks for a one-pager, quick take or flash note | one page, in this order: decision box, beat/miss table with revenue and EPS variance, EPS-quality verdict, debate map, changed estimate lines with old against new. Delivered in chat unless the user asked for a document, and as a DOCX through .agents/skills/docx/SKILL.md when they did. No chart minimum |
| Debate map alone | the whole ask is the call or the Q&A | the transcript Q&A map and the debate map, each side carrying a falsifier tied to a dated catalyst. Delivered in chat, no report and no charts around them |
A mode is chosen once and holds, and a shorter mode is rebuilt at that depth rather than truncated (.agents/skills/research-conventions/references/depth.md). Missing inputs never shorten the note: a missing artifact stays visible as a labelled gap in the section that wanted it, using the absence vocabulary below.
The length budget, the chart count and the DOCX assembly belong to the deep dive. A short mode is complete on the contract in its own row; the freshness gate, the evidence contract and the tier 1 hard fails in references/best-practices.md bind every mode.
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.
- 1mo ago Changed · -129 lines · +53 tokens per session 2fd962bcd4f4
- 1mo ago First seen · 230 lines · 23 tokens per session scan A c0514b9564be
earnings-analysis is a skill published in the GitHub repository ginlix-ai/LangAlpha (2,155 stars, last pushed today), licensed Apache-2.0. It adds 76 tokens to every session and 1,791 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to earnings-analysis, differing in 246 lines, and is treated as a copy.
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