Build a source-derived writing style profile from real posts, essays, launch notes, docs, or site copy, then reuse that profile across content, outreach, and social workflows. Use when the user wants voice consistency without generic AI writing tropes.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Brand Voice
Build a durable voice profile from real source material, then use that profile everywhere instead of re-deriving style from scratch or defaulting to generic AI copy.
## When to Activate
- the user wants content or outreach in a specific voice
- writing for X, LinkedIn, email, launch posts, threads, or product updates
- adapting a known author's tone across channels
- the existing content lane needs a reusable style system instead of one-off mimicry
## Source Priority
Use the strongest real source set available, in this order:
1. recent original X posts and threads
2. articles, essays, memos, launch notes, or newsletters
3. real outbound emails or DMs that worked
4. product docs, changelogs, README framing, and site copy
Do not use generic platform exemplars as source material.
## Collection Workflow
1. Gather 5 to 20 representative samples when available.
2. Prefer recent material over old material unless the user says the older writing is more canonical.
3. Separate "public launch voice" from "private working voice" if the source set clearly splits.
4. If live X access is available, use `x-api` to pull recent original posts before drafting.
…
The line at the top of this page pins the label git:20260918.c752aac, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
A 17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the 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 (3637 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
affaan-m/ecc · 284,510 stars · license MIT · pushed 2026-10-20 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_q2jwjpwvzpadjh6d
GET https://markdownregistry.com/api/v1/resolve?ref=affaan-m/ecc/brand-voice
GET https://markdownregistry.com/api/v1/blob/63bb7231f1ec358dcd6b4d9c8bceb212d3c2475be2dd2b8336e3c265bc6d5c03
Your AI assistant 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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