article-level2

name: article-level2 description: Convert one L1 source entry into one L2 explanation (briefing-document) article in Japanese — the agent-workforce equivalent of the GAS L1→L2 batch. Use when an editorial-stream agent must turn an uncovered L1 source into a faithful, evidence-grounded explanation: an Executive Summary up front, source-specific section headings, and every number/name/date/quote taken verbatim from the source. Published to Notion as Type=explanation, Author={agent_slug}, Status=ready.

article-level2

Convert one L1 source entry into one L2 explanation article in Japanese.

This is the agent-workforce counterpart of the GAS L2_BATCH / handleL2Create pipeline (newsletter/gas/src/Code.gs). The GAS path fetches a source URL, builds a briefing-document prompt, calls Azure, and writes an explanation-type row into the unified Notion Articles DB. This skill produces the same deliverable — a faithful briefing-document explanation — attributed to the running agent so the article carries a byline on kohuehara.xyz.

It runs on the CCR execution model (the same pattern as Dario's feed-post): the binding is executor=claude-code-routine + scheduler=external/api, fired every 2 hours by wf-orchestrator-tick into the generic agent-runner routine (workforce/docs/routines/agent-runner.md). The routine composes your persona + this skill body, you generate the explanation, then a bundled write script owns the Notion write — you do not hand-edit any file and do not open a PR.

Two Notion DBs, one credential (apiKey only)

This skill reads the L1 source library and writes the unified Articles DB — two different databases. Only the Notion apiKey is a secret; the two database ids are not secret (they're already committed in newsletter/gas/src/Code.gs and newsletter/pipeline/normalize-categories.mjs), so the scripts hold them as constants. You therefore need just one injected credential:

The Notion integration behind apiKey must be shared with both databases in Notion. (L2 and L3 share the unified Articles DB, distinguished by Type; a future article-level3 skill reuses the same credential + unified DB. L1 is the one genuinely separate DB — its id is a constant in pick-l1-source.mjs.)

Instructions

1. Pick one uncovered L1 source — run the picker, don't guess. Run pick-l1-source.mjs (below). It queries L1 + the unified DB and returns the oldest L1 source whose Source URL no explanation covers yet (same filters as handleL2Batch). If it returns {"skip": true, …}, stop — produce nothing this fire. Otherwise use the returned {title, summary, sourceUrl} as your subject. Ground every claim in that source (fetch sourceUrl for the body when it's reachable; otherwise work from summary only — see Hard rules).

   NOTION_API_KEY="<credentials['notion.integration_token'].apiKey>" \
     node workforce/skills/article-level2/pick-l1-source.mjs
   

2. Produce one Japanese briefing-document explanation (target ~3000 字).

3. Follow the L2 briefing format (identical to the GAS buildL2Prompt contract):

   • Line 1: a # H1 — a concrete Japanese title specific to the source's subject. No generic placeholders ("AIの可能性", "変化への対応" are banned).
   • Directly below: a ## Executive Summary section — a 2–3 sentence lead surfacing the single most important takeaway before the reader scrolls.
   • Body: 2–5 ## sections, each named after a source-specific theme. Separate evidence (facts from the source) from conclusion (the implication you draw). Use short paragraphs plus bullet lists carrying the actual numbers, names, dates, and direct quotations.

4. Do not append a bias-disclosure footer (or any byline boilerplate) to the body. Disclosure is carried by the Author metadata — rendered as the AuthorChip byline on kohuehara.xyz — the same policy feed-post already follows (Epic-011 §7 / Q9). In-body boilerplate duplicates that metadata, freezes a model id in prose, and was the trigger for the ML-006 deploy-gate false positive.

Hard rules (editorial integrity — C-1, fail loud — C-4)

• Never invent facts. Every concrete figure, proper noun, date, or quotation must come verbatim from the supplied source. Do not abstract, round, or alter them.
• For JS-only / paywalled hosts (x.com, twitter.com, linkedin.com, and CDN consent-wall sites like nytimes/ft/wsj/bloomberg/mckinsey), fetch via Jina Reader first: https://r.jina.ai/<source-url> returns pre-extracted clean Markdown. This mirrors the GAS L2_SOURCE_FETCH_VIA_READER routing in newsletter/gas/src/Code.gs — a direct fetch of these hosts returns 402/HTML-bot-walls, but the Jina-extracted body is groundable. Only fall back to the L1-summary-only path if Jina also fails.
• If the source body still could not be fetched, work from the L1 summary only and do not supply facts, statistics, company names, or people the summary doesn't contain.
• If you cannot link to or quote the source, do not publish — escalate.
• Objective, incisive tone. Avoid reviewer-voice hedges ("重要だ", "今後注目される") and throat-clearing preambles.

Write the article — run the script, do NOT hand-edit any file

The page is written by a deterministic script, not by you editing JSON. You generate the judgment (the briefing-document markdown); publish-notion.mjs owns the write (correct schema, properties, block conversion) by POSTing a new page into the unified Articles DB with the injected integration token.

Steps:

1. Write the full explanation markdown to a temp file (e.g. /tmp/l2-article.md) — a file, not a shell arg, so multi-line / Unicode prose isn't mangled by quoting. The first line must be the # Title H1 (used as the page Title and stripped from the body blocks).

2. Write the abstract — a faithful 2–3 sentence lead (your ## Executive Summary, not the speculative L1 summary) — to a second temp file (e.g. /tmp/l2-abstract.txt). This populates the Abstract column, matching how other rows lead.

3. Run (the script writes to the unified Articles DB — its id is a built-in constant, so only NOTION_API_KEY is needed). Pass the picker's category (a bare A–E letter) — the script canonicalises it to "B: Role Blurring" etc. and fills both Category and CategoriesMulti, exactly like the GAS L2 write:

   NOTION_API_KEY="<credentials['notion.integration_token'].apiKey from your task>" \
     node workforce/skills/article-level2/publish-notion.mjs \
       --author "<agent_slug>" \
       --type explanation \
       --status ready \
       --body-file /tmp/l2-article.md \
       --abstract-file /tmp/l2-abstract.txt \
       --category "<category from the picker, e.g. B>" \
       --source-url "<sourceUrl from step 1>"   # omit if none
   

4. Report the script's exit code:

   • 0 — page created. The row carries Author={agent_slug}, Type=explanation, Status=ready, plus Abstract + Category/CategoriesMulti (queued; the GAS L4 batch flips Status to published). Done.
   • 2 — W-1 editorial guard failed (empty/short body, LLM-artefact prelude, or a last line that looks cut off mid-content — the shared scripts/lib/truncation.mjs heuristic), or 401/403 auth (project credential bag misconfigured). Read stderr; do not retry blindly. A sentence ending wrapped in emphasis (*…。*) is a valid ending — if the guard trips, the body really is cut off; regenerate the ending.
   • 1 / 3 — bad args / missing H1 title, or Notion API / network error.

NOTION_API_KEY comes from your task's injected credentials["notion.integration_token"].apiKey — never read it from anywhere else, never hard-code it. (The DB ids are non-secret constants inside the scripts.) The script re-runs the W-1 guards before writing, so a degraded body fails loudly rather than landing on the site.

The page lands directly in Notion. No PR, no human-approval gate. The page is written to the unified Articles DB with the live schema (Title, Author and SourceURLs as rich_text, Type/Status as select, Date) — the same property contract as the GAS L2 write. The existing GAS L4 batch picks up the row and publishes it to kohuehara.xyz; newsletter/pipeline/fetch-notion.mjs surfaces Author

• Type into the front-end manifest so AuthorChip renders the byline.

When NOT to use

• A source already covered by an existing L2 explanation — skip and pick the next uncovered entry (the GAS coverage check keys on source URL).
• A test/placeholder source (example.com) — never flows to L2.
• A source whose original text is a one-line headline only — escalate, do not pad.