Home / ginlix-ai / langalpha · plugins/langalpha_research/skills/earnings-preview/SKILL.md · GitHub

earnings-preview skillA

earnings-preview is agent-read markdown (skill) from ginlix-ai/langalpha: Pre-print setup for a company about to report: the expectation bar, EPS-quality watch, call questions, scenarios and the reaction framework. Triggers on earnings preview, what to watch for [company] earnings, pre-earnings setup, preview Q[N]..

Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.

What the file says

# Earnings Preview

Everything in this note locates the stock against one object: the **bar**, the level of results the market is already positioned for. Consensus is one input to the bar, not the bar itself. The preview says where the bar sits, what could clear or miss it, what to listen for on the call, and what the reaction is likely to be if the print lands each way.

After the print, route to `.agents/skills/earnings-analysis/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.

## Route

The full preview is the default. A short version is produced only when the user asks for one, and it is rebuilt at the lower depth rather than truncated (`.agents/skills/research-conventions/references/depth.md`): the freeze time, the source posture, the bar numbers, the top two debates, the must-watch call questions and the missing-evidence block all survive the rebuild.
…

Read the whole file at its exact version.

How to install

Latest version
mdr add ginlix-ai/langalpha/earnings-preview@git:20260921.26f807b
Exact content
mdr add ginlix-ai/langalpha/earnings-preview@sha256:eae3e1327d229d5f

Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_phas24srlq2pwabs.svg)](https://markdownregistry.com/a/art_phas24srlq2pwabs)

1 badge views in 30 days

Versions

versioncommittedcommitsizeaudit
git:20260921.26f807b latest2026-09-21 26f807b 14,750 BA view · diff
git:20260915.b214b522026-09-15 b214b52 14,765 BA view · diff
git:20260826.8da358a2026-08-26 8da358a 3,325 BA view

Audit of the latest version

A  17 of 17 checks passed. Deterministic, no model, same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (14750 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

ginlix-ai/langalpha · 1,774 stars · license Apache-2.0 · pushed 2026-09-24 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_phas24srlq2pwabs
GET https://markdownregistry.com/api/v1/resolve?ref=ginlix-ai/langalpha/earnings-preview
GET https://markdownregistry.com/api/v1/blob/eae3e1327d229d5f436789f57a52ebd2bd619e8746ade2b2b3be24596bf1199e

Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

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