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episode

Split one source post into tier-sized drafts (teaser, main social post, longread, technical dev-log) with cross-links downward and a canonical link back to the repository. Draft-first: publishes nothing itself. Triggers: "/episode", "/adapt", "adapt this post", "make an episode".

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EPISODE_ADAPTER (stage S5 of content factory v2 — the contract [[decision-content-pipeline-reality-show]] §7.2)

GOAL: ONE source post → an "episode" = one draft PER (tier × platform) from §7.2, with cross-links downward and canonical→GitHub baked in. Draft-first: we write drafts and publish NOTHING.

THE §7.2 CONTRACT (implemented 1:1):

tier      length          platforms (phase 1)                    language   voice/model
teaser    240-370 (HARD)  RU channel · X (EN)                    RU TG/EN X  authorial · Opus
medium    800-2500        Facebook (RU)                          RU          authorial diary · Opus · LINK IN THE 1ST COMMENT (not in the body) + a question
longread  4000+ narrative RU channel·VC.ru·Habr(RU) · GitHub(EN) RU and EN  authorial reality-show · Opus
dev-log   a dry log       GitHub (EN, canonical)                 EN          technical, impersonal · Sonnet scaffold + Opus for cohesion
  • The owner's voice (authorial) = Opus ONLY. The dev-log is not authorial — Sonnet assembles it, Opus stitches it together.
  • canonical = the GitHub markdown on every platform (a single source of truth for AI). Repo: github.com/tonydzi/clawrush.
  • NO copy-paste — every file is a NATIVE rewrite for its platform.
  • Cross-links downward: teaser→longread; medium→longread (in the 1st comment); longread ←teaser →dev-log; dev-log→longread + an anchor to our Deep Research.
  • THE PLATFORM DECIDES THE LANGUAGE (there is no bilingual pair on every tier).
  • The S3 narrative ([[style-reality-show]]) by tier: teaser=cold open+cliffhanger; medium=a full episode arc; longread=an extended episode+recap; dev-log=raw material, no drama.
  • The cofounder CTA (medium+longread, the owner's rule, memory [[cofounder-cta-public-contact]]): WhatsApp +1 341 222 9178 = an authorized PUBLIC contact (a privacy carve-out), never strip it.
  • VC.ru + Habr (the RU geo longread) = phase 1 since 2026-07-04 (the style files _STYLE-vcru.md/_STYLE-habr.md are written and live in content-factory\; the writer loads them by the pointer in the placeholder). PHASE 2 (deferred): only Reddit (the EN geo dev-log) — scaffolded with the --with-phase2 flag.

PATHS:

  • ⭐ FACTS AND CONTINUITY (v2, 2026-07-10) = THE SINGLE CANON $OBSIDIAN_VAULT/04-Projects\show-canon\: before assembling an episode, read the anchor beat (beats\) plus its arcs/loops — "previously on the show", the cliffhanger and the season question come FROM THERE (not from memory, not from SHOW-STATE, which is frozen). Respect the beat's reveal axis: don't burn live_hold/spoiler_until. Pick the next move with /reality-show next. After publishing — write the consequences back into the beat + run canon_render.py.
  • Source material: $IMPORTS_ROOT/content-factory/triage/posts.md (📝) — or a topic the owner names.
  • The scaffolder (deterministic, 0 tokens): $IMPORTS_ROOT/content-factory/episode_adapter.py.
  • Bundles: episodes\<slug>\ (8 .md files in phase 1 / 9 with --with-phase2 + meta.json; every §7.2 field is baked into the placeholders).
  • Style: [[style-reality-show]] (08-Templates\style-reality-show.md) + 04-Projects\personal\facebook-diary-auto\_STYLE.md + [[style-Mei-influence]] + the golden corpus up to 2023.

STEPS:

  1. PICK the topic: if the owner named one, use it; otherwise show the 📝 items from posts.md and take the strongest thread. Run list before new.
  2. SCAFFOLD: python episode_adapter.py new --slug <kebab> --title "<title>" --source "hub:<id>" (+--with-phase2 for VC.ru/Habr/Reddit) → a bundle of empty drafts + meta.json.
  3. WRITE (the model is named in each placeholder): teaser-ru/en, medium-fb (the body WITHOUT the link + a "1ST COMMENT" block), longread-ru/en, devlog. Replace the stubs, leave the hint comments in place. Privacy is strict (the only carve-out is the cofounder's WhatsApp).
  4. CHECK (the visibility layer): python episode_adapter.py check --slug <slug> — lengths (a teaser outside 240-370 = HARD FAIL; medium/longread = WARN), CTA present, empty files. Only FAIL=0 → step 5 (a WARN on an unfinished longread is acceptable until it is written out).
  5. REVIEW (draft-first): set-status --slug <slug> --status review; into Telegram Saved (chat_id <YOUR_CHAT_ID>, account "work_acct_a", no parse_mode): "🎬 Episode '<title>' — the per-tier drafts are ready (check ✅). episodes<slug>. Say 'publish' and I'll lay them out." NOTHING goes outward.
  6. EXPORT TO PUBLISHING — only on the owner's explicit "publish"/"+" (Tier-2): python episode_adapter.py export --slug <slug> → drafts\episode-<slug>.md (format type: content-factory-draft + the registers ## -> TG/X/FB). From there the EXISTING path: content_approve.py --serve → content_publish.py (→ Saved; the real channels are Phase 2b/Tier-2). GitHub/Reddit/VC.ru/Habr are published MANUALLY (gh / natively), not through content_publish. We do NOT breed a second publisher.

LIMITS:

  • Draft-first OUTWARD: channels/X/GitHub are untouched without an explicit "publish".
  • MODEL: the authorial voice = Opus ONLY; dev-log = Sonnet+Opus; scaffold/check/export = deterministic, 0 tokens.
  • One post = one episode. Windows cp1252: the script forces UTF-8 stdout itself.
  • Don't invent facts — write from the real source material.
  • Old bundles (4-file / interim) are still read by list/show/check/export through meta (backward compatibility).
<!--kit-footer-->

Like this skill? It is one of 100 in second-brain-starter-kit: the second brain we built for ourselves and run every day at Palo Alto AI Research Lab. Install the whole set with npx skills add tonydzi/second-brain-starter-kit. Everything is open source and free, so take what you need.

Flagships worth a look on their own: secondop-panel (a second opinion from a panel of external models), claude-memory-tidy (stop your agent's memory from rotting), telegram-mcp-kit (your own Telegram over MCP in about 15 minutes).

Author: Anton Dziatkovskii, Palo Alto AI Research Lab. Telegram @tonydzi - WhatsApp +1 341 222 9178 - X @Tony_Stef_

Engineers: want to test-drive this setup? Message me. I hand out free starter seeds to engineers who test and report back, and custom skill requests are welcome.

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