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Research To Wechat

v0.5.5

A native research-first pipeline that turns a topic, notes, article, URL, or transcript into a sourced article with an evidence ledger, polished Markdown, in...

2· 555· 11 versions· 0 current· 0 all-time· Updated 34m ago· MIT-0

Install

openclaw skills install research-to-wechat

Research to WeChat

<!-- // TODO: split SKILL.md into smaller modules/components -->

Use this skill as a native, research-first article system. It does not route execution to external skills.

Core Rules

  • Match the user's language.
  • Ask one question at a time.
  • Ask only when the answer changes source interpretation, structure frame, style fidelity, or draft delivery behavior.
  • Keep Markdown as the canonical article asset until the HTML handoff.
  • Save a draft only. Never publish live.
  • Separate verified fact, working inference, and open question.
  • Every major claim must be traceable to a source.
  • Every article must end with a "## 参考链接" or "## References" section listing all sources.
  • Apply the full normalization checklist before HTML rendering.
  • Every inline image must pass a two-tier evaluation: eliminate defects first, then verify content match.
  • the renderer converts [text](url) into text (url) because WeChat forbids clickable links.
  • Never pretend the workflow did interviews, long field research, team debate, or hands-on testing when it did not.
  • Prefer visible disclosure of AI assistance and source scope.
  • Treat source capture as a runtime boundary: preserve title, author, description, body text, and image list before rewriting.

Operating Paths

  • Path A: research-first article use for: topic, keyword, question, notes, transcript, subtitle file goal: build the article from a research brief and evidence ledger

  • Path B: source-to-WeChat edition use for: article text, markdown file, article URL, WeChat URL goal: preserve the useful source core, then rebuild it for WeChat reading and distribution

Default routing:

  • procedural or tool-teaching material -> tutorial
  • thesis, trend, strategy, critique, case material -> deep-analysis
  • multi-topic roundup -> newsletter

Accepted Inputs

  • keyword, topic phrase, or question
  • notes, outline, or raw material dump
  • article text
  • markdown file
  • PDF paper, report, or whitepaper
  • article URL
  • WeChat article URL
  • video URL
  • full transcript
  • subtitle file that can be expanded into a full transcript

PDF policy:

  • extract all figures, charts, tables, and diagrams as image assets
  • save extracted figures to imgs/source-fig-*.png
  • record captions and page numbers in source.md
  • prefer source figures over generated visuals when they support the claim

Video policy:

  • a video source is valid only when the workflow can obtain the full spoken transcript
  • first attempt transcript recovery from the page, captions, or subtitle assets
  • if no full transcript is obtainable, ask for the transcript or subtitle file and wait

Output

Create one workspace per article: research-to-wechat/YYYY-MM-DD-<slug>/

Required assets:

  • source.md
  • brief.md
  • research.md
  • article.md
  • article-formatted.md
  • article.html
  • manifest.json
  • imgs/cover.png
  • inline illustration files referenced by the markdown body

Required frontmatter in final markdown:

  • title
  • author
  • description
  • digest
  • coverImage
  • styleMode
  • sourceType
  • structureFrame
  • disclosure

manifest.json must capture:

  • pathMode
  • styleMode
  • structureFrame
  • sourceType
  • confidence
  • draftStatus
  • output paths

manifest.json.outputs.wechat must include:

  • markdown
  • html
  • cover_image
  • title
  • author
  • digest
  • images

Script Directory

Determine this SKILL.md directory as SKILL_DIR, then use ${SKILL_DIR}/scripts/<name>.

ScriptPurpose
scripts/fetch_wechat_article.pyWeChat article fetch (mobile UA)
scripts/wechat_delivery.pyNative WeChat delivery entrypoint (check, design-catalog, render, upload-images, save-draft)
scripts/install-openclaw.shOpenClaw skill installer

Native Capability Contract

This skill executes every stage itself:

  • source ingest via bundled fetch script, browser tools, and PDF inspection
  • markdown polish via normalization rules in this skill
  • inline visual planning and cover direction via native article analysis
  • design catalog compile via python3 "${SKILL_DIR}/scripts/wechat_delivery.py" design-catalog
  • WeChat HTML rendering via python3 "${SKILL_DIR}/scripts/wechat_delivery.py" render
  • image upload via python3 "${SKILL_DIR}/scripts/wechat_delivery.py" upload-images
  • draft save via python3 "${SKILL_DIR}/scripts/wechat_delivery.py" save-draft
  • multi-platform distribution via native browser/API steps when Phase 8 is requested

Use the internal contract in capability-map.md.

Delivery Ladder

Resolve WeChat draft delivery in this order:

  1. L0 official-http: WECHAT_APPID and WECHAT_SECRET are ready, so bundled scripts call the official media and draft APIs directly
  2. L1 assisted-browser: only use a browser when the account setup or draft inspection needs human help
  3. L2 manual-handoff: stop with exact file paths and required API fields when official delivery cannot proceed

Author Config (EXTEND.md)

The renderer reads an optional EXTEND.md for author-specific CTA content and preferences. This keeps the skill generic — CTA text, QR codes, and blog URLs belong to the author, not the skill.

Lookup order: project dir → ~/.config/research-to-wechat/~/.research-to-wechat/

See author-config.md for the full format and field reference.

When EXTEND.md is present with a cta section, the renderer appends a styled CTA block after the article body. When absent, no CTA is rendered.

Style Resolution

Resolve style in this order:

  1. explicit user instruction
  2. preset mode
  3. author mode
  4. custom brief

Use the full style system in style-engine.md.

Visual rendering is decided by:

  • styleMode
  • structureFrame
  • light or dark output mode

Execution

Run the article through these phases:

  1. intake and route selection

  2. source packet, brief, and strategic clarification

  3. research architecture with structured question lattice

  4. research merge and evidence ledger

  5. frame-routed master draft with normalization checklist, writing self-check, and machine-verified Chinese de-AI scan (Phase 5 must not proceed without running these):

    # negation-contrast patterns (must be 0 hits)
    grep -n '不是.*而是\|不仅.*而且\|不只.*更\|不再.*而是\|已经不是' article-formatted.md
    # em-dash count (≤5 in body)
    grep -c '——' article-formatted.md
    # exclamation marks (must be 0)
    grep -c '!' article-formatted.md
    
  6. 微信敏感词合规检查(⛔ 必须通过才能继续):用 wechat-compliance-check 扫描 article-formatted.md,有命中则改写后重新扫描,直到零违规。

  7. refinement, visual strategy, and image evaluation

    ⛔ Pre-delivery compliance gate (BLOCKING — must execute before Phase 8): Long sessions cause attention decay on early-loaded rules. Before proceeding to HTML rendering and draft save, you MUST:

    1. Re-read the project's AGENTS file (cat the file, do not rely on memory). For WeChat projects this is ../AGENTS-wechat.md or the path specified in AGENTS.md.
    2. Walk every rule in the AGENTS file line by line and verify the current article/HTML against it. Check file location, typography, HTML constraints, CTA, image rules — every single one.
    3. Output a checklist to the terminal with ✅/❌ per rule. Any ❌ must be fixed before continuing. This step exists because context-window attention decay will cause you to forget rules loaded at session start. Do not skip it. Do not check from memory.
  8. native WeChat HTML rendering via wechat_delivery.py render, image upload, draft save, and manifest.

    Image upload rules:

    • If imgs/cdn-urls.json already exists from a previous upload, skip re-uploading unchanged images. Only upload new or modified files (compare filename + file size/mtime).
    • wechatqr.png (CTA QR code) must reuse the existing CDN URL from project-level images/wechatqr.png or a previous cdn-urls.json. Never re-upload the same QR code per article.
    • After upload, always merge new CDN URLs into the existing cdn-urls.json (not overwrite).

    Draft save rules:

    • If manifest.json already contains a media_id, pass --media-id to save-draft to update the existing draft. Never create a duplicate.
    • If a duplicate draft was accidentally created, delete it via API (draft/delete) immediately and keep only the original media_id.
    • manifest.json is the single source of truth for media_id.

    Before draft save, run HTML compliance check (must all pass):

    grep -c 'class=' article.html          # must be 0
    grep -c '<style' article.html          # must be 0
    grep -c '<a href' article.html         # must be 0
    # outermost <section> must have background
    python3 -c "import re;h=open('article.html').read();m=re.search(r'<section[^>]*>',h);print('OK' if m and 'background' in m.group() else 'FAIL')"
    

    Known issue: render collapses newlines inside <code> blocks. The renderer converts markdown fenced code blocks into single-line <code> content, stripping all \n characters. Multi-line code will display as one long line. Detection: python3 -c "import re;h=open('article.html').read();codes=[c for c in re.findall(r'<code>(.*?)</code>',h,re.DOTALL) if len(c)>80 and '<br' not in c];print(f'{len(codes)} collapsed code blocks' if codes else 'OK')" Fix: extract code blocks from the source markdown (which preserves newlines), HTML-escape them, replace \n with <br/>, and substitute back into the rendered HTML. WeChat ignores literal \n in HTML — only <br/> produces visible line breaks. This must run after render and before save-draft.

    Known issue: render outputs <thead> without dark background. In dark mode, table headers render with browser-default white/transparent background, making header text invisible. Fix: add background:#1E293B (or the design's surface color) to <tr> and <th> inside <thead>. Also ensure <td> has explicit background matching the page background.

    Known issue: render duplicates ordered list numbering. Markdown 1. 2. 3. becomes <ol><li>1. text</li> — the <ol> auto-numbers AND the literal 1. prefix remains. Fix: strip the leading N. from each <li> content.

    Known issue: render keeps the H1/H2 title in the HTML body. WeChat article titles are set via the draft API title field, not in the HTML body. The renderer copies the markdown # title into an <h2>. Per WeChat typography rules, this must be removed. Fix: delete the <section> containing the <h2> that matches the draft title.

    Known issue: --upload-map may not replace all image paths. After rendering with --upload-map, verify that zero src="imgs/" local paths remain. If any survive, do a string replace pass in post-processing. Detection: grep -c 'src="imgs/' article.html must be 0.

    Known issue: reference link section has oversized letter-spacing on mobile. The body line-height:1.9 and font-size:15px cause long URLs in the reference section to spread out on mobile. Fix: override the reference section <p> tags with font-size:13px;line-height:1.6;word-break:break-all;text-align:left.

    File path rule: always follow the project's AGENTS file for output directory. This skill defaults to research-to-wechat/YYYY-MM-DD-<slug>/. If the project AGENTS specifies a different convention (e.g. YYYY-MM-DD-<slug>/ at project root), the project rule overrides this skill's default. Check the project AGENTS before creating the workspace directory.

  9. optional multi-platform content generation and distribution

Phase 9 only executes when the user explicitly requests it.

Use the execution contract in execution-contract.md. Use the platform copy specs in platform-copy.md for Phase 8.

Done Condition

The skill is complete only when all of these hold:

  • the article reads as researched before it reads as polished
  • the route choice and structure frame fit the source instead of forcing one house style
  • the chosen style is visible without collapsing into imitation
  • the writing framework self-check for the chosen frame has been applied
  • the evidence ledger clearly separates fact from interpretation
  • every visual adds narrative or explanatory value
  • the normalization checklist has been applied: no citation artifacts, no LaTeX, no broken tables, no scraped UI remnants
  • every image placeholder was evaluated against placement criteria before generation
  • every generated or selected image passed the two-tier quality check
  • markdown and HTML agree on title, summary, cover, and image paths
  • HTML contains zero class= attributes, zero <style> tags, zero <a href> links, and outermost <section> has explicit background
  • manifest.json agrees with the actual output set and draft state
  • the article does not overclaim research effort or authorship
  • wechat-compliance-check returned zero violations on the final markdown
  • the workflow can stop safely at the highest-quality completed artifact if a later handoff fails
  • if Phase 8 was triggered, platform copies follow platform-copy.md and manifest includes their output entries

Version tags

latestvk9795crav58t31twy2e4tks67x8504pb

Runtime requirements

🔬 Clawdis
Any binpython3
Primary envWECHAT_APPID