feat(linkedin): v2.2.0 — harden longform gates from 2nd production run
Implements the 6-change spec from the Seres-serien production (linkedin-plugin-endringsspec.md). All acceptance criteria met. 1. Avoid-patterns (modell-/navne-katalog, completeness-over-reader-action, self-referential overhead openings) → longform-quality-rules.md (rule 1+3) + user-profile.template.md. 2. Persona gate now BLOCKING with explicit hard-fail list (primær mistet meg / doesn't own action / sjargong-mur / modell-navne-katalog → BLOCK; "JA med store forbehold" = NEI) → persona-reviewer.md + personas.template.md. 3. Fact-check declared orthogonal to narrative strength + post-cutoff web-search mandate + high-frequency-error checklist → fact-checker.md. 4. NEW agent voice-scrubber.md (Opus) — de-AI scrub + Norwegian-chronicle voice-drift; gold standard = approved Norwegian editions, NOT the English post corpus. Wired into newsletter.md Step 4. 5. Operator gates = render+annotate rounds (build-html.mjs to file://) as primary flow, AskUserQuestion as receipt/fallback → newsletter.md 2.5+3a. 6. Edition state reconciled with STATE.md (ONE-system). edition-HANDOVER template deleted; narrative to <serie>/STATE.md, machine data (factcheckLog, personaSweep, immutableRules) to edition-state.json. Agents 14 to 15; commands unchanged (24). Backward-compatible (additive state-shape only). Docs updated across all three levels + CHANGELOG. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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@ -50,6 +50,30 @@ Before searching, identify:
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- **Out of scope:** Opinions, predictions, and value judgments are NOT claims to
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verify. Mark them as opinion and move on — do not score them.
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**Fact-check is orthogonal to narrative strength.** The more convincing a draft
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reads, the MORE source-verification it needs — not less. A fluent, confident
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passage is exactly where a wrong fact hides best; never let polish lower the bar.
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**Post-cutoff mandate (non-negotiable).** Any claim dated *after the model's
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knowledge cutoff* — a recent appointment, a 2025/2026 figure, a just-announced
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product, a current title — **MUST be web-searched.** Never confirm such a claim
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from memory; memory cannot contain it. An unsearched post-cutoff claim defaults
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to 🟡 at best, 🔴 if precise.
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**High-frequency error types — check these explicitly:**
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- **Person titles / roles** — someone may have left, changed role, or never held
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the title claimed. Verify the title *as of now*, not as of training.
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- **«Standards» that actually vary** — practices presented as universal often
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differ per organization/jurisdiction. Flag a claimed standard that is really a
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local convention.
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- **Studies credited with too-strong findings** — a study cited as proving X
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often only suggested X, or measured something narrower. Check what it actually
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concluded.
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- **Source scope** — distinguish what a source *concluded* from what was *outside
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its scope*. A source silent on X does not support a claim about X.
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- **Start / founding / release years** — dates of founding, launch, or release are
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frequently misremembered by a year or more. Verify the exact year.
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### Step 2: Search for Primary / Credible Sources (3-5 searches per claim)
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Prefer primary sources (the originating document, dataset, or official record)
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@ -207,7 +231,9 @@ Aggregate the per-claim verdicts into a publish decision:
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2. **Never fill gaps with guesses.** No invented sources, no plausible numbers.
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"Cannot verify" is a complete, acceptable answer.
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3. **Search before judging.** Never assign a verdict without running searches.
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Web search is non-negotiable.
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Web search is non-negotiable — and **mandatory** for any claim dated after the
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model's knowledge cutoff (titles, recent figures, new releases). Memory cannot
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verify what postdates it.
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4. **Primary over secondary.** Trace claims to the originating document, not the
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blog post that summarized it.
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5. **Precision matters.** "Exactly 37%" needs an exact source; a directional
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