Home / ginlix-ai / langalpha · plugins/langalpha_research/skills/model-update/SKILL.md · GitHub

model-update skillA

model-update is agent-read markdown (skill) from ginlix-ai/langalpha: Refresh an existing financial model after a print, a guidance change, a consensus move, a filing, a KPI release or a capital-structure change. Triggers on update the model, roll it forward, the new quarter is out, revise estimates, refresh the price target..

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

# Model Update

Updating is not building. You know what changed in the world and you do not know what the file will do when you write into it, so the order below maps every data point to a treatment before a single cell moves, keeps the file the user gave you byte-identical, and leaves a reader able to see what changed and on whose authority.

Evidence labels, source tiers, staleness, the readiness posture and the intake limits: `.agents/skills/research-conventions/SKILL.md`, read before the first write.

Routing before you start:

- The workbook's own `Checks` sheet fails, or the model looks wrong before you touch it: audit it first with `.agents/skills/check-model/SKILL.md`.
- The refresh has to move operating metrics rather than the three statements: `.agents/skills/dcf-model/references/sector-drivers.md` lists what drives each sector.

## Step 1: Name the trigger and list the fields it touches

One update has one trigger. Name it, hold the document or the tool call that carries it, and write down the fields it reaches before opening the workbook.

| Trigger | Arrives as | Touches |
|---|---|---|
…

Read the whole file at its exact version.

How to install

Latest version
mdr add ginlix-ai/langalpha/model-update@git:20260921.26f807b
Exact content
mdr add ginlix-ai/langalpha/model-update@sha256:aaa01ed8b777fcb7

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_nkqo4fm763x5n3n3.svg)](https://markdownregistry.com/a/art_nkqo4fm763x5n3n3)

1 badge views in 30 days

Versions

versioncommittedcommitsizeaudit
git:20260921.26f807b latest2026-09-21 26f807b 12,231 BA view · diff
git:20260915.99ad8262026-09-15 99ad826 12,261 BA view · diff
git:20260826.8da358a2026-08-26 8da358a 3,146 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 (12231 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_nkqo4fm763x5n3n3
GET https://markdownregistry.com/api/v1/resolve?ref=ginlix-ai/langalpha/model-update
GET https://markdownregistry.com/api/v1/blob/aaa01ed8b777fcb7abc19a3b02c96ad0aa300443de63a361c626b85562684cca

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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