인터페이스는 현지화되어 있으며, Skill 소개와 설명 문서는 선택한 언어로 AI가 자동 번역합니다. 코드·명령어·경로·전문 용어는 원문을 유지하며 원작자 문서가 우선합니다.
Skills 둘러보기
개발 및 엔지니어링 · SKILL.md

repurpose-all

repurpose-all

Orchestrator — one topic, drafts across every format in one pass. Default produces LinkedIn, Twitter, Newsletter, GitHub Pages, Medium, Substack. Skips per-skill clarifying questions using sensible defaults. Use when a topic is worth posting in multiple places and you don't want to invoke each skill separately.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: repurpose-all description: Orchestrator — one topic, drafts across every format in one pass. Default produces LinkedIn, Twitter, Newsletter, GitHub Pages, Medium, Substack. Skips per-skill clarifying questions using sensible defaults. Use when a topic is worth posting in multiple places and you don't want to invoke each skill separately.

repurpose-all

You are drafting one topic across multiple formats in a single response. This is an orchestrator over the six format-specific skills in this plugin. Use it when the topic is genuinely worth posting in multiple places and you want to avoid invoking each skill one-by-one.

Step 1 — Load context (mandatory)

Read the shared voice files ONCE:

  1. shared/voice-rules.md
  2. shared/voice-samples.md
  3. shared/pet-peeves.md
  4. shared/topic-modes.md
  5. shared/platform-styles.md

Then read each format's SKILL.md to load its rules and delivery shape:

  1. ../linkedin-write/SKILL.md
  2. ../twitter-write/SKILL.md
  3. ../newsletter-write/SKILL.md
  4. ../github-page-write/SKILL.md
  5. ../medium-write/SKILL.md
  6. ../substack-write/SKILL.md

Also load the LinkedIn hook formulas:

  1. ../linkedin-write/references/hook-formulas.md

Step 2 — Ask format selection (one question only)

Ask the user ONCE:

"Generate which formats? Default is all six (linkedin, twitter, newsletter, github-page, medium, substack). Reply with all, or a comma-separated subset like linkedin,twitter,medium."

Wait for the answer. Default to all if no response.

Step 3 — Detect emoji level from invocation

Parse the user's original invocation for an emoji override: "no emoji", "low emoji", "medium emoji", "high emoji". If none specified, default to low. Apply the chosen level uniformly across every generated format (each format already honors its per-format ceiling per shared/voice-rules.md).

Step 4 — Apply sensible defaults (do NOT ask the user per format)

The point of this orchestrator is to avoid six rounds of clarifying questions. Apply these defaults silently:

FormatDefault
linkedinlength = medium (~1300 chars)
twittermode = opinion (single tweet preferred, 2-tweet mini-thread if needed)
newsletterlength = default (300-600 words)
github-pagetheme = warm-light, unless topic-mode classifier says security → dark-cyberpunk
mediumlength = default (1500-3000 words)
substacklength = default (600-1200 words)

For github-page, do not generate a full HTML file in this orchestrator response. Instead, output a Markdown skeleton: title, dek, numbered section headings with 1-2 paragraphs each, code blocks where they belong. Tell the user that if they want the final HTML, invoke github-page-write separately on the same topic and it will produce the styled file.

Step 5 — Classify topic mode

Apply shared/topic-modes.md once. Use the resulting mode (security / architecture-agents / leadership / cost-infra) consistently across all formats. The mode shifts register per voice-rules.md:

  • Security topics → forensic across all formats. GitHub theme defaults to dark-cyberpunk.
  • Architecture/agents → sharp technical opinion.
  • Leadership/governance → measured, evidence-first.
  • Cost/infra → pragmatic-flex (specific number + ship outcome).

Step 6 — Draft each requested format

For each selected format, apply the rules from its SKILL.md. Reuse the same core argument across formats — DO NOT invent different conclusions for different platforms. The topic's thesis is constant; the structure, length, and register adapt.

Adaptation principles:

  • Apply each platform's row from shared/platform-styles.md. The thesis is constant, but technical depth, headline aggressiveness, and density visibly differ across the six outputs. A reader seeing the X post and the GitHub page side by side should feel they were written for different rooms: X atomic and shallow, GitHub deep and dense, Medium a curiosity-gap title over honest prose. Respect the precedence rules in that file.
  • Same hook family across LinkedIn / Twitter (opinion mode) / Substack — they can share a hook line or close variants.
  • Twitter quote / wow are reductions of the core observation. Twitter thread is the LinkedIn-medium post compressed into 4-6 numbered tweets.
  • Newsletter is the LinkedIn-medium argument with a subject line and slightly more breath.
  • Medium / GitHub Pages are the same argument expanded with sections, citations, and at least one code/config block if technical.
  • Substack sits between LinkedIn-sharp and Medium-measured. Use a pull-quote.

Pet peeves apply to every format. Run the regex sweep from shared/pet-peeves.md against every draft before delivering.

Step 7 — Save all formats into a single drafts directory

Derive a kebab-case topic slug from the user's topic. Get today's date in YYYY-MM-DD form. Create the directory:

./drafts/<YYYY-MM-DD>-<topic-slug>/

Save each generated format as its own file in this directory:

  • linkedin.md
  • twitter.md
  • newsletter.md
  • medium.md (Markdown only here; Medium does not parse Markdown, so the paste-ready medium.html is produced only when the user invokes medium-write separately)
  • substack.md
  • github-page-skeleton.md (the Markdown skeleton — the styled HTML is produced only when the user invokes github-page-write separately)

If the directory already exists (re-running on the same topic same day), suffix the directory with -v2, -v3, etc.

Step 8 — Deliver

Deliver one consolidated response with each format under its own delimiter. Use this exact structure:

═══════════════════════════════════════
TOPIC: <one-line topic restatement>
TOPIC MODE: <security | architecture-agents | leadership | cost-infra>
FORMATS: <list>
EMOJI LEVEL: <none | low | medium | high>
SAVED TO: ./drafts/<YYYY-MM-DD>-<topic-slug>/
═══════════════════════════════════════

─── LINKEDIN ─────────────────────────
<post body>

ALTERNATE HOOKS:
- <hook 1>
- <hook 2>

meta: <chars> chars · hook pattern: <name>

─── TWITTER ─────────────────────────
<tweet body OR thread with 1/, 2/, ...>

meta: <chars>/280 · mode: opinion

─── NEWSLETTER ──────────────────────
subject: <≤8 words>
preheader: <≤120 chars>

<body>

meta: <words> words

─── GITHUB PAGE (Markdown skeleton) ─
# <title>
> <dek>

## 1. <Section>
<paragraphs>

## 2. <Section>
<paragraphs>

<...>

## The Short Version
<3-line distillation>

meta: theme = <warm-light | dark-cyberpunk> · est <N> min read
note: run `github-page-write` to produce the styled HTML file.

─── MEDIUM ──────────────────────────
# <title>
> <dek>

<opening paragraph>

## <H2 1>
<...>

## The Short Version
<...>

meta: <words> words · <N> min read

─── SUBSTACK ────────────────────────
subject: <≤8 words>
dek: <one sentence>

<body>

meta: <words> words · <N> min read

═══════════════════════════════════════
DONE. <one-line note on what the user should review most carefully — e.g., "GitHub skeleton is structural only; run github-page-write next for styled output.">
═══════════════════════════════════════

Skip any format the user didn't select. Keep the delimiter blocks for the ones included.

Step 9 — One pre-delivery check

Confirm all of these in one pass before sending the response:

  • Every format applies the same core thesis. No contradicting takes between platforms.
  • Pet peeves regex sweep passes for every draft.
  • First-person throughout, no engagement-bait, no em-dash sentence joiners.
  • The Topic Mode is consistent.
  • Each format applied its platform-styles.md row — depth, headline, and density visibly differ across formats (subject to topic-mode overrides), and no headline produced engagement-bait.
  • Emoji level applied consistently across formats (and per-format ceilings respected).
  • Every file in the drafts directory was written.

Anuj reviews and copies to each platform manually. Do not auto-post anywhere.

저장한 Skills