L’interface est localisée ; les présentations et documents des Skills sont traduits automatiquement par IA dans votre langue. Le code, les commandes, chemins et termes techniques restent en version originale, et le document de l’auteur fait foi.
Explorer les Skills
Développement · 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

Documentation de la Skill

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.

Skills enregistrées