Home / notque / vexjoy-agent · skills/content/content-engine/SKILL.md · GitHub

content-engine skillA

content-engine is agent-read markdown (skill) from notque/vexjoy-agent: Repurpose source assets into platform-native social content..

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

# Content Engine Skill

Repurpose anchor content into platform-native variants. This skill produces drafts only — it does not make API calls or publish content. Posting is handled downstream by `x-api` (single platform) or `crosspost` (multi-platform).

Platform-native means each variant is written from scratch for its target platform: different register (conversational on X, professional-but-human on LinkedIn, punchy on TikTok), different structure (thread vs. long-form post vs. short script vs. newsletter section), and different hook style (open fast on X, strong first line on LinkedIn, interrupt on TikTok). Shortening the same text for each platform is not adaptation — it produces content that reads identically everywhere and fails on every platform.

## Instructions

### Phase 1: GATHER — Collect Inputs Before Writing Anything

Establish everything needed to write platform-native variants. Do not begin writing until this phase is complete.

**Required inputs:**

| Input | Description | If Missing |
|-------|-------------|------------|
| Source asset | The content being adapted (article text, demo description, launch doc, insight, transcript) | Ask — required |
…

Read the whole file at its exact version.

How to install

Latest version
mdr add notque/vexjoy-agent/content-engine@git:20260919.28d30f9
Exact content
mdr add notque/vexjoy-agent/content-engine@sha256:5d46ac2f5ed3ac40

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_zyidqfymwptnwp6m.svg)](https://markdownregistry.com/a/art_zyidqfymwptnwp6m)

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Versions

versioncommittedcommitsizeaudit
git:20260919.28d30f9 latest2026-09-19 28d30f9 8,339 BA view · diff
git:20260705.380563c2026-07-05 380563c 9,189 BA view · diff
git:20260610.60dbf442026-06-10 60dbf44 9,159 BA view · diff
git:20260529.9747fea2026-05-29 9747fea 9,103 BA view · diff
git:20260506.42e7d622026-05-06 42e7d62 8,759 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 (8339 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

notque/vexjoy-agent · 424 stars · license MIT · pushed 2026-09-23 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_zyidqfymwptnwp6m
GET https://markdownregistry.com/api/v1/resolve?ref=notque/vexjoy-agent/content-engine
GET https://markdownregistry.com/api/v1/blob/5d46ac2f5ed3ac40cf678422d238d288a435c0427cd7c7f79a5d9d5fbd5f5a77

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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