feat(linkedin-studio): N7.5 — MR-F9 etterspørsels-sveip (Tier-5-kilder + smertepunkt + vokabular-oversettelse + arc-kontrakt) [skip-docs]

The «innenfra og ut» demand-sweep: the mechanism that FILLS the N6 reader fields
(readerQuestion/painPoint/saturation). Discovery finds "what happened"; this layer
translates it into "the problem the reader is stuck on".

- demand-spotter agent (agents 19->20, inherits session): three passes after
  discovery, before drafting — demand-sweep -> pain-point map -> vocabulary translation.
- Tier 5 demand sources in config/trends-sources.template.md (inverse of Tier 1-4;
  honest blind spots: YouTube API, Reddit approximate, HN/GitHub ground truth).
- demand signal on TrendRecord (strength + answered) — rankable twin of the verbatim
  saturation text; additive-optional, store schema stays v4 (no migration).
- arc.ts (§4 output contract): groupIntoArcs (relatedIds transitive closure),
  rankArcQuestions (etterspørsel x kan-svare x ikke-besvart), classifyMarketGap
  (supply-gap != demand-gap != saturated). Pure + deterministic (TDD).
- arcs CLI verb + /linkedin:trends --demand mode (commands stay 30); morning brief
  shows the per-candidate demand signal.

Suites: trends 276->300, test-runner 139->140, tsc clean. Others unchanged
(brain 134, hooks 140, tests 35, render 60).

MR-F9 built (bygget-men-ubevist) — the (a)/(b)/(c) evidence gate is a runtime
demonstration, proven consumer-side (plugin agents don't resolve in the dev repo).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_014bE7VbkmR3cqHFEeGfzgwb

config/trends-sources.template.md

@@ -57,6 +57,19 @@ grouped by tier. Keep `Name — URL — note` so a poll can cite the URL.
 - [Earnings / report calendar] — [url] — scheduled releases
 - Seasonal themes: [Q1 …] · [Q2 …] · [Q3 …] · [Q4 …]
 
+## Tier 5 — Demand signals (where the questions live) — the demand-sweep polls these
+
+*Tier 1–4 are SUPPLY sources — they tell you what was announced. Tier 5 is the inverse: where
+your audience already **asks**. The `demand-spotter` agent («innenfra og ut») polls these to turn a
+topic into the reader's own question, its pain point, and an honest saturation verdict. Ground truth
+first (HN + GitHub APIs are exact); forums are approximate; some channels need an API (see the notes).*
+
+- [Practitioner forums / communities] — [url] — where people ask (Reddit, HN, product forums, Discord/Slack where reachable). *Reddit blocks direct fetch → counts are approximate; HN via the Algolia API is exact.*
+- [GitHub issues on the spec/tool repos] — [url] — undervalued gold: real questions from the people building, with names + comment counts as signal strength (GitHub API = ground truth)
+- [Procurement data] — [url] — the hardest demand indicator there is: someone has a budget and wrote the need down (e.g. a national tender portal / TED-equivalent for your market)
+- [Regulator / supervisory guidance] — [url] — what your reader is *required* to take a position on (non-optional demand)
+- [Comment fields on your channels] — [url] — *NB: YouTube/video comments are JS-rendered → need an API key; the largest blind spot. Specify the fetch method or mark the channel explicitly un-swept — an honest null is a finding.*
+
 ---
 
 ## Your niche additions