wayamzpost

name	wayamzpost
description	Generate one Amazon-seller post tailored to a specific platform — Xiaohongshu (default, 6-9 cards), LinkedIn (long-form text, ≤3000 chars, 3-5 hashtags), X / Twitter (single tweet ≤280 chars OR thread of up to 25), or Instagram (1-10 carousel + ≤2200 char caption). Each platform has its own char limits, hashtag rules, card count range, and post.md output layout. Supports Chinese (default) or English output via config.output_language. Trigger when the user says "写小红书 amazon post / 亚马逊小红书 / amazon seller post / linkedin amazon post / x amazon thread / instagram amazon carousel" or asks for a platform-specific seller-audience post. Generates artifacts only; does NOT auto-publish unless the user explicitly enables a publish adapter in their config.
version	1.8.0

wayamzpost

Generate one Amazon-seller-audience post per day, tailored to a specific platform: Xiaohongshu (default — 6–9 deterministic image cards), LinkedIn (long-form text), X / Twitter (single tweet or thread), or Instagram (1–10 carousel + caption). Output is a publish-ready markdown file (post.md) plus rendered PNGs for carousel platforms — the user uploads manually.

HARD RULES (read these first)

1. No automated publishing by default. This skill stops at producing cards/*.png and post.md. Never call any XHS publish flow, playwright_publish_*, or external upload tooling unless the user explicitly sets publish_adapter.enabled = true in their config and provides a module_path. See references/publish-adapter.md.
2. Config is mandatory. First-run users must copy config.example.json to ~/.config/wayamzpost/config.json (or wherever; set WAYAMZPOST_CONFIG=<path>) and fill in persona.brand_cn. Existing installs that still use XHS_AMAZON_CONFIG or ~/.config/amazon-xhs-poster/config.json remain supported as a legacy fallback. The validator refuses to run while it still says REPLACE_ME. Pick output_language: "zh" or "en" AND platform: "xiaohongshu" | "linkedin" | "x" | "instagram" here — they change the title keyword, CTA tokens, char limits, hashtag rules, card count range, and post.md output layout. See references/platforms.md.
3. Voice supremacy. When any pattern in the references would force a sentence the persona wouldn't say, drop the pattern, write the natural line, and append the reason to post.json.qa_notes. Mechanical rule-following degrades copy faster than it protects it.
4. Confidentiality boundary. Public copy must not leak any token from config.forbidden_source_tokens (paid feed names) or config.forbidden_brands_in_copy (your internal tooling). The validator hard-fails on either.
5. Manual decisions belong to the user. Pick the angle, write the draft, render the cards — but never auto-confirm "this is good enough to post" without showing the user the rendered output and post.md.

What you produce

<config.paths.drafts_root>/<DATE>/
├── research/
│   ├── topic.md                # angle + sources, drives editorial
│   ├── recent_history.json     # 30-day rolling, dedup data
│   └── recent_history.md
├── cards/
│   ├── card_01.html …          # source HTML (debug)
│   ├── card_01.png …           # 1080×1440 PNGs ready for upload
│   └── render_manifest.json
├── post.json                   # canonical post artifact
└── post.md                     # final hand-off file (title / body / hashtags / card list)

Optionally mirrored to <config.paths.desktop_root>/<DATE>/ for AirDrop/iCloud sync to phone.

Workflow (6 stages)

Stage 0 — Initialize the day

In every command below, ${SKILL_DIR} is the install path of this skill — typically ~/.claude/skills/wayamzpost. Substitute literally before running, or export SKILL_DIR=~/.claude/skills/wayamzpost first.

python3 ${SKILL_DIR}/scripts/init-day.py [--config <path>] [--date YYYY-MM-DD]

Creates the day's directory tree, writes the post.json skeleton (persona from config), and runs history.py to generate recent_history.{json,md}. Defaults today to America/Los_Angeles. Idempotent — re-running on the same date reuses the existing files.

Stage 1 — Research & angle selection

Follow prompts/research-stage.md:

1. Read research/recent_history.md.
2. Apply the 14-day rotation in references/angle-rotation.md to pick today's topic.category.
3. Find a sharp topic in that category; gather 2–5 real https:// source URLs from the Tier ladder in references/editorial-sop.md. Tier A (public, dated, automation-friendly) and Tier B (public, no listing dates) are the day-to-day candidates. Tier C (gated; X / LinkedIn / wearesellers / BDS / Walmart corp news / YouTube creator-signal) is automated via fetch-gated.mjs if the user has it enabled — see the "Optional gated-source pipeline" section below.
4. Write research/topic.md and fill post.json.topic (category, angle, why_now, selection_reason, sources).

Stage 2 — Editorial (write post.json)

Follow prompts/editorial-stage.md:

1. Pick title and CTA patterns per references/title-and-cta-patterns.md (T1–T8 / CTA1–CTA6, respecting 7-day title and 3-day CTA rotation).
2. Write 6 cards (expand to 7–8 only if needed) per the schema in references/card-schema.md. Each card has id, kind, eyebrow, headline, body, bullets, footer.
3. Write xhs.title (≤ 20 chars, must contain configured keyword), xhs.content (with hashtag block appended), xhs.tags (5–10, tiered).
4. Voice supremacy: if any pattern fights the persona, drop it and document in qa_notes. See references/voice-and-persona.md.

Stage 3 — Render cards + Validate

node ${SKILL_DIR}/scripts/render.mjs <DRAFTS_ROOT>/<DATE>/post.json [--config <path>]

The renderer:

• Runs validate.py first; render proceeds only on exit 0.
• Generates card_01.png … card_0N.png at 1080×1440 via Playwright.
• Mirrors to desktop_root/cards/ if configured.
• Writes back status.render = "done" into post.json.

If the validator hard-fails, fix post.json and re-run. Soft-warnings are informational; review them but don't block.

To run the validator manually any time:

python3 ${SKILL_DIR}/scripts/validate.py <DRAFTS_ROOT>/<DATE>/post.json --json

Stage 4 — QA (Tier C taste check)

Answer all 4 before declaring done:

1. Does card 1 stop the scroll in 3 seconds?
2. Can a busy seller decide a concrete action in 30 seconds?
3. Does a first-time visitor get a credible reason to follow?
4. Does the post feel like "this account filters 90% of the noise"?

Any "no" → return to Stage 2.

Stage 5 — Hand-off

python3 ${SKILL_DIR}/scripts/make-post-md.py <DRAFTS_ROOT>/<DATE>/post.json

Produces post.md at <job_dir>/post.md. The user opens this on their phone and uploads to Xiaohongshu manually.

⛔ Stage 6 — Auto-publish (DEFAULT: DISABLED)

Only run if config.publish_adapter.enabled === true AND module_path is set. See references/publish-adapter.md. Read that doc fully before enabling — getting bot-flagged is a real risk.

Optional gated-source pipeline

When config.gated_sources.enabled = true, the skill ships a 6-fetcher research pipeline that pulls structured signal into <job_dir>/research/gated-signal.md for Stage 1 to fold into topic.md. Disabled by default — automating logged-in services has real ToS / account-suspension risk. Read references/gated-sources.md before enabling.

The 6 fetchers (run in one command):

Source	Auth needed?	What it pulls
X / Twitter	Real Chrome (CDP)	Recent tweets from configured handles
LinkedIn	Real Chrome (CDP)	Recent activity from configured profile slugs
wearesellers.com	Real Chrome (CDP)	Top hot non-paid threads with body extraction
billiondollarsellers.com	Real Chrome (CDP)	Top archive articles (subscribers see body)
corporate.walmart.com	Public	Top recent news via news.sitemap.xml
YouTube	Real Chrome (CDP)	Recent videos from configured channel handles

Setup (one-time):

# 1. Launch a separate Chrome with debug port enabled.
#    NOTE: this uses a dedicated debug profile and leaves your normal
#    Chrome session alone.
bash ${SKILL_DIR}/scripts/launch-chrome-debug.sh

# 2. In that Chrome, log in to: x.com, linkedin.com, wearesellers.com,
#    billiondollarsellers.com.  YouTube + Walmart are public.

# 3. Daily fetch:
node ${SKILL_DIR}/scripts/fetch-gated.mjs --connect-cdp [--date YYYY-MM-DD]

Output: <drafts_root>/<DATE>/research/gated-signal.md. Editorial stage folds relevant items into topic.md and post.json.topic.sources[].

Source-decay audit

Public Tier A/B URLs bit-rot. Run monthly to catch decay:

node ${SKILL_DIR}/scripts/audit-sources.mjs            # full report
node ${SKILL_DIR}/scripts/audit-sources.mjs --quiet    # only flagged
node ${SKILL_DIR}/scripts/audit-sources.mjs --json     # machine-readable

Hits all 11 Tier A/B URLs with plain fetch(), reports HTTP / size / last-seen date, flags 4xx, redirects, suspiciously small payloads, and content older than 90 days. Exits non-zero on any flag.

Quick triggers (when to invoke)

• "写小红书 amazon post" / "亚马逊小红书" / "xhs amazon" / "来一篇亚马逊笔记"
• "amazon seller post" / "amazon creator note"
• "linkedin amazon post" / "linkedin amazon thread"
• "x amazon post" / "amazon twitter thread" / "amazon x thread"
• "instagram amazon carousel" / "ig amazon post"
• Any request to produce a platform-specific Amazon-seller-audience post

Quick triggers (when NOT to invoke)

• AI-builder digest / 9-card AI content (different methodology)
• Single-image (non-carousel) XHS posts
• Video content
• Non-Amazon-seller audiences

Platform support

Set config.platform to one of:

Platform	Format	Title cap	Body cap	Hashtags	Cards
xiaohongshu	image carousel	20 chars	(soft)	5–10	6–9
linkedin	long-form text	(none)	3000	3–5	0
x	post or thread	(none)	280/post	0–2	0
instagram	carousel + caption	(none)	2200	5–30	1–10

Every platform supports both output_language: "zh" and "en". They are independent fields. So language=zh + platform=linkedin produces Chinese LinkedIn posts; language=en + platform=x produces English X threads. For X specifically, the validator applies CJK weighting (each Chinese char counts as 2 toward the 280 weight cap, per twitter-text spec).

See references/platforms.md for the full language × platform matrix, post.json shape (especially xhs.thread for X), per-platform editorial guidance, and cross-posting workflow.

Dependencies

• Python 3.9+ (for zoneinfo)
• Node.js 18+
• Playwright with Chromium: npx playwright install chromium

Tree

wayamzpost/
├── SKILL.md                    (this file)
├── README.md                   (install + first-run; user-facing)
├── config.example.json         (zh-default; copy and fill)
├── config-en.example.json      (en-default; copy if output_language="en")
├── references/
│   ├── editorial-sop.md        (Tier A/B/C/D source ladder + workflow)
│   ├── angle-rotation.md
│   ├── title-and-cta-patterns.md
│   ├── card-schema.md
│   ├── voice-and-persona.md
│   ├── customization.md
│   ├── platforms.md            (per-platform limits + workflow)
│   ├── gated-sources.md        (X/LinkedIn/wearesellers/BDS/Walmart/YouTube auto-fetch)
│   └── publish-adapter.md
├── prompts/
│   ├── research-stage.md
│   └── editorial-stage.md
├── scripts/
│   ├── init-day.py             (Stage 0; platform-aware skeleton)
│   ├── history.py              (called by init-day; safe to call alone)
│   ├── validate.py             (Stage 3 gate; reads PLATFORM_PRESETS)
│   ├── render.mjs              (Stage 3; skips when cards is empty)
│   ├── make-post-md.py         (Stage 5; per-platform output layout)
│   ├── fetch-gated.mjs         (optional Stage 1 helper; 6 fetchers via CDP)
│   ├── launch-chrome-debug.sh  (one-shot launcher for fetch-gated CDP attach)
│   └── audit-sources.mjs       (monthly Tier A/B URL decay check)
└── examples/
    ├── post.example.json                (xiaohongshu / ZH canonical)
    ├── post-en.example.json             (xiaohongshu / EN)
    ├── post-linkedin.example.json       (linkedin / EN)
    ├── post-linkedin-zh.example.json    (linkedin / ZH)
    ├── post-x.example.json              (x / EN thread)
    ├── post-x-zh.example.json           (x / ZH thread)
    ├── post-instagram.example.json      (instagram / EN)
    ├── post-instagram-zh.example.json   (instagram / ZH)
    └── persona.example.json             (alternate persona block)