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Personal brand content

Skill dzhokhov/markdown-agent-vault/skills/personal-brand-content

Agent-ready Markdown vault methodology with AGENTS.md, templates, skills, logs, and file-safe workflows.From the repository description

Install
npx -y skills add dzhokhov/markdown-agent-vault --skill personal-brand-content

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

4.4 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it

Skill: Personal Brand Content

Appointment

Creating and adapting expert content for a personal brand or expert channel. Skill helps: generate content from the queue, adapt the master version for a specific platform, maintain a single voice of the author.

When to use

Triggers:

  • Write a post about [theme] for [platform]
  • Adapt [content] to [platform]
  • “new idea: [text]”
  • "to post what?"
  • "handle backlog"
  • «weekly review»
  • "update metrics"

Project context

Must read before work:

  1. <project>/context.md – niche, audience, pillars, formats
  2. <project>/pipeline.md is a content process methodology.
  3. <project>/platforms/{platform}.md – target platform profile, if available

Voice of the author (Author Voice)

**Expert, but accessible. Like talking to a smart colleague over coffee.

** Principles:**

  • Specifics > abstraction. It was always “the result” and not “AI is the future.”
  • Experience > Opinion. Tell me what you did, not what you think.
  • Use > hype. Each post should give something useful: tool, approach, insight.
  • Honesty > positivity. Do not hide failures and limitations
  • Simplicity > smartness. Difficult things in simple language

** Forbidden:**

  • Empty words, cliches, and bureaucratic phrasing
  • "In the modern world ...", "It's no secret that ...", "We all know ..."
  • Clickbait headlines without content
  • General advice without specifics
  • Self-praise without evidence

Content creation process

Step 1: Identify introductory

Read the idea from the backlog or the user request. Determine:

  • Content pillar (pillar)
  • Format
  • Target platform(s)

Step 2: Create a master version

Write the full version of the content without format limitations. Turn on:

  • Title (3 options)
  • Main text with specifics
  • CTA (if appropriate)
  • Sources/links

Save in: content/YYYY-MM-DD-slug-master.md

Step 3: Adapt to the platform

Download the platform profile from platforms/{platform}.md. Adapt:

  • Length (by platform limits)
  • Formatting (markdown, HTML, plain text)
  • Tone (more/less formal)
  • Hashtags/tags
  • CTA (subscription, comment, repost – by platform patterns)

Save in: content/YYYY-MM-DD-slug-{platform}.md

Step 4: Final check

  • Check the text for empty words, cliches, bureaucratic phrasing, and lack of specifics
  • Verify compliance with the platform profile
  • Check for specifics (digits, cases, tools)

Working with a bank of ideas

The command "new idea: [text]"

  1. Read ideas/ideas-backlog.csv
  2. Identify the next id
  3. Add a line with: date added, source (user-input), title, the rest is empty.
  4. Confirm to the user

The "handle backlog" team

  1. Read ideas/ideas-backlog.csv
  2. Find records with status=draft and empty pillar/format
  3. For each: offer pillar, format, platforms
  4. Calculate the score using the ICE pipeline model.
  5. Show the user to confirm
  6. Update the CSV

The post-what command?

  1. Read ideas/ideas-backlog.csv
  2. Filter status ) {draft, processed} (not published, not rejected)
  3. Sort by priority score DESC
  4. Show the top 5 with: title, pillar, format, platforms, score
  5. Ask the user what they choose.

Working with metrics

The command "Update the metrics [post]"

  1. Ask the user for current numbers (views, likes, comments, shares, new followers, link clicks)
  2. Add a line to analytics/metrics-log.csv with snapshot time
  3. Confirm.

Weekly review team

  1. Read analytics/metrics-log.csv in the last 7 days
  2. Read ideas/ideas-backlog.csv in the last week.
  3. Create a review from a template from pipeline.md (Weekly Review section)
  4. Save it to analytics/YYYY-Wnn-review.md.
  5. Propose adjustments to the strategy

Related skills

  • Signal Selection Skill or Separate List of Ideas – A Source of Topics for Expert Content, If It’s in Storage
  • translation-editorial] Translation-editorial signals into content
  • case-forensics — extracting cases for content]

References

Platform profiles (completed via Q&A with NotebookLM):

  • references/messenger-best-practices.md
  • references/linkedin-best-practices.md
  • references/facebook-best-practices.md
  • references/vc-ru-best-practices.md
  • references/habr-best-practices.md
  • references/reddit-best-practices.md

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most marketing audience skills give in ~1.1k tokens

Counted across 690 of the 894 authors here whose files we hold, read 2026-08-07

  • Apply Poppins font to headingsin 41 of 690, across 6 files
  • Apply Lora font to body textin 41 of 690, across 6 files
  • Use Arial fallback for headingsin 39 of 690, across 4 files
  • Use Georgia fallback for body textin 39 of 690, across 4 files
  • Maintain text hierarchy and formattingin 39 of 690, across 4 files
  • Use accent colors for non-text shapesin 38 of 690, across 3 files
  • Use RGB values for precise color matchingin 38 of 690, across 3 files
  • Use brand colors for primary text and backgroundsin 36 of 690, across 1 file
  • Read product marketing context file before asking questions, starting, or auditingin 35 of 690, across 23 files
  • Use active voice instead of passive voicein 26 of 690, across 10 files
  • Implement or generate appropriate JSON-LD structured datain 24 of 690, across 17 files
  • Prioritize clarity over clevernessin 22 of 690, across 8 files

Said here and by no other author read

  • Write a full master version without format limits
  • Adapt the master version for the target platform
  • check the text for empty words and lack of specifics
  • verify compliance with the platform profile
  • add new ideas to the backlog csv
  • offer pillar format and platforms for draft ideas

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 326,790. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.