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Author SHA1 Message Date
8c91c409cd fix(linkedin-studio): N22 — ærlighetsscrub (fabrikkerte benchmarks, Velocity Score, 15+-terskelen) [skip-docs]
Tre defektklasser av samme slag: tall som ser sourcet ut, men ikke er det.

Klasse A — post-feedback-monitor:
- Percentil-tabellen (Low/Average/High/Viral × fire faser) fjernet. Ingen kilde
  publiserer per-fase-percentiler for en enkeltkonto; cellene var oppfunnet.
  Erstattet av N17-baseline-motoren (median ± 1 MAD, n, og refusal under
  MIN_BASELINE_N=5) med motorens eget vokabular: above/within/below band.
- Velocity Score fjernet i sin helhet, inkl. fase-multiplikatorene (5,0x/3,0x/
  1,5x/1,0x/0,5x). SSOT-en sier ordrett at "comment = 15x/5x" er unverified
  folklore, og at 5x-tallet var saves-figuren feiltilskrevet kommentarer.
  Erstattet av rå tellinger + engagement rate slik csv-parser.ts definerer den.
- Output-malen har nå en eksplisitt refusal-gren. Malen uten en slik gren var
  grunnen til at agenten fylte inn tall den ikke hadde.
- To folklore-multiplikatorer i Principles ("5x the impact", "worth 15 likes").

Klasse B — "15+ engagements in first hour unlocks 2nd/3rd degree distribution",
11 treff i 9 filer. SSOT-en sier "Directional, not a fixed threshold". Påstanden
overlevde både hardening-gaten og kald-review (log.md:1099 sjekket ~70%-
misattribusjonen, ikke terskelen).

Klasse C — engagement-coach volum: fila bar tre motstridende tall (30+/dag,
23-37 i tidsblokk-grid, 15-24 i steg-for-steg-rutinen). Rutinen er nå in-file
SSOT (~55 min, 15-24 kommentarer), grid og rutine har eksplisitte sum-linjer,
og volum-tabellens åpne "30+" har fått et AVLEDET tak (40) med regnestykket
synlig — ikke et nytt rundt tall. Uverifiserbar superlativ ("110K followers,
#2 global creator") fjernet.

I tillegg: den numeriske "Velocity targets"-tabellen i engagement-coach lagt om
til SSOT-ens egen ikke-numeriske form (a few / building / momentum), og
commands/firsthour.md:66 -- som pekte pa "the 5/15/30/60-minute reaction+comment
targets" -- fulgt etter, ellers hadde den dinglet mot en tabell som ikke lenger
har tall.

docs/hardening/log.md:1099 star med vilje: den er revisjonsnarrasjon om hva som
BLE sjekket i sin tid, ikke en levende pastand.

Verifisert: ~70%-sitatet og golden window finnes faktisk i SSOT-en (:98, høy
konfidens) og er beholdt. Alle ti suiter grønne, floors uendret.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_017Pwb1oWLqKB2oBJHSoWNcy
2026-07-31 18:35:25 +02:00
885526738c fix(linkedin-studio): N21 — scaffold-bånd-redesign + ferskhet-rester (newsletter-guide, first-comment) [skip-docs]
Del 1 — scaffold-bånd (KTG-beslutning: behold målbåndet, utvid komponentene).
Komponentsummen var 960–1 640 mot målbåndet 1 200–1 800: en skjelett-konform
draft kunne lande under gulvet og nådde aldri taket. Nye bånd — Context
250–350, Insight 550–850, Implication 250–350 (Hook 110–140 og CTA 50–100
uendret) — summerer til 1 210–1 790, altså INNI 1 200–1 800. Skjelett-konform
er nå gate-konform per konstruksjon.

Målbåndet 1 200–1 800 er uendret overalt; hooks/prompts/content-quality-gate.md
(den kanoniske gaten) er ikke rørt. Alternativet — å heve taket per AuthoredUp
D-4 — ville krevd 25 filer / 40 linjer inkl. gate-prompten, begge skills,
quality-scorecard, config-malen og brain-fiksturen.

Skjelettet fantes i seks kopier, alle rettet på KTG-go: commands/post.md,
commands/batch.md, commands/pipeline.md, references/engagement-frameworks.md,
agents/content-optimizer.md, skills/linkedin-content-creation/SKILL.md. De tre
siste lå utenfor planens scope, men to av dem var internt selvmotsigende på én
linje (overskrift 1 200–1 800 over komponenter som summerte til 960–1 640), og
engagement-frameworks.md er nettopp fila post.md/pipeline.md instruerer
modellen om å LESE for strukturen.

Nabofunn tatt med på KTG-go: post.md:95 ga «Personal stories → 1 000–1 400»,
som motsa post.md:136s egen gate. Kald-review R2a MAJOR — nå 1 200–1 800.

D-4 inn i kanonfila: ny «Post length»-seksjon i
references/algorithm-signals-reference.md med AuthoredUp-optimumet 1 301–2 500
(372 126 poster, sep 2025–feb 2026), merket single-vendor/ett vindu, med
eksplisitt note om at datapunktet gjør det shippede taket konservativt — ikke
feil — og at de to AuthoredUp-N-ene i fila (621K vs 372K) er ulike studier.
Kilde verifisert mot primærkilden, ikke overført fra planen.

Del 2 — ferskhet-rester (begge påstander verifisert mot LinkedIn Help):
- D-6 newsletter-strategy-guide.md: «5 000+ følgere» framstilt som terskel er
  feil — «All LinkedIn members have access to create a newsletter on LinkedIn»
  (a517914). Omskrevet til redaksjonell modenhetsvurdering (også i
  Mistakes-tabellen og Bottom Line). E-post er ikke garantert: LinkedIn
  de-dupliserer på tvers av kanaler — «if you receive an in-app or push
  notification, you should not expect to also receive an email for the same
  notification» (a517914). Bringer referansefila i tråd med newsletter.md:2384.
  Fjernet samtidig den ukildede «Algorithm favors newsletters from established
  creators» i den omskrevne blokka.
- D-7 first-comment-strategy.md: «pinned by default» er uverifisert og feil —
  pinning er en eksplisitt forfatterhandling (a524166), og standard
  kommentarsortering er algoritmisk. Lagt til «What this file does not claim»-
  avsnitt som speiler kanonfilas «contested»/low-confidence-epistemikk.

Scope 3 (KTG-go, amend): references/engagement-frameworks.md har FIRE
skjeletter, ikke ett. To til brot gulvet i malbandet — Data-Driven Post
(1 050-1 400) og Contrarian Post (1 060-1 410) — og er lagt om til samme
komponentprofil som Standard, sum 1 210-1 790. Narrative Arc (1 350-1 500) la
allerede inni og star urort; alle tre har na en eksplisitt sum-linje. Fila er
den post.md:104 sender modellen til for «story structures», sa a sertifisere
den som fikset med to odelagte skjeletter igjen ville vaert usant.

SUPERSEDED og ikke gjeninnført: gammel B §S6 Del 2 pkt 1 (first-comment
−5/−10 %-tall, pods-eskalering, 360Brew-fotnote).

Verifisering: bånd-summen ligger inni målbåndet i alle seks kopier av
standard-skjelettet og i alle fire skjelettene i engagement-frameworks.md
(grep-bevis, 0 gjenværende 200-300/400-800) · D-6/D-7 omformulert (0 treff på
«5,000+ followers» / «pinned by default» / «inbox + email») · alle ti suiter
grønne, alle floors uendret: test-runner 270/0 (269 assertions >= floor 251) ·
trends 300/0 · analytics 202/0 · hooks 191/0 · brain 134/0 · editions 72/0 ·
render 63/0 · specifics-bank 45/0 · tests 35/0 · contract-gate 33/0.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01LhF1H7ctT5Fk8KkoCQpe5n
2026-07-31 18:08:53 +02:00
e75cd42bed feat(linkedin-studio): de-niche rest-sweep — vary KTG-beat examples across surfaces (B-S2b) [skip-docs]
The last de-niche slice: recast the 10 sites where the vendor/sector beat
(Microsoft|Azure|Copilot|public sector) sat as the PRIVILEGED/default example,
varying each to a concrete cross-domain example instead of sterilizing
(plugin-is-domain-general — domain comes from user config, never hardcoded).

Recast (10): url-processing-templates (news worked-example Copilot->Figma),
opportunity-generation (3 headline examples + About block -> varied/ops persona),
profile (3 "good example" headlines/impact -> healthcare/e-commerce/support),
first-comment-strategy (drop "Microsoft" from research-paper example),
poll-strategy-guide (Copilot option -> generic AI assistants),
engagement-frameworks (1 of 3 direct-address audiences -> RevOps/SaaS),
setup (audience e.g. -> two varied examples), post (invocation e.g. -> SaaS pricing),
network-builder (tagline example -> ops/manufacturing),
video-scripter (2 filename slugs -> neutral topics).

Kept as false positives (would sterilize): content-angles.md (Public Sector is
1 of 6 balanced industry tables + Industry-Agnostic section), outreach.md
(Microsoft Build/Ignite/Azure UG = 3 of ~20 varied real conferences),
linkedin-growth-playbook (biographical fact in a real case study), the
Gemini/Tavily/Perplexity MCP tool-name examples, and the algorithm-signals
"Gemini provenance" SSOT citation. AI-as-topic kept (not a niche token; the
de-AI/AI-slop mechanic is the plugin's legit subject).

Gate scripts/test-runner.sh 87/0/0 (no lint touches these files yet; §17-guard
extension to content-planner is the deferred next step). 10 files, 26/26.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01RBMKqPSVbvSZHtQ4heM1UY
2026-06-23 10:50:28 +02:00
e17134ee9b refactor(linkedin-studio): S31c descriptive-%-scrub — platform-norm percentages asserted as fact -> SSOT
24 edits / 12 files (+26/-26). Unsourced platform/algorithm/audience percentages reconciled to
SSOT vocabulary (figure/proportion/multiplier unverified). Catalog + new sibling clusters
(64% follow-up x5, wrong-window 70% x4, Stage-2 6-10% x2) + borderlines (70% retention, 70%
mobile) + the ~3% save-worthy straggler (surfaced, not silent). The SSOT-sourced ~70% reach
figure is KEPT; only the wrong window corrected (60min/1h -> first 15-30 min). Sourced/computed
benchmarks kept (Buffer 178%/247%, Socialinsider 11%). KEPT C1: ~45% AI-comment figure (already
hedged correlational/medium-confidence). Gate 81/0/0 exit 0, counts 29/19/26 + v0.5.0.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_016qgzo6rxthw7KuxHjn5vyE
2026-06-20 09:54:44 +02:00
25b356fc5c fix(linkedin-studio): S29c terminology-scrub — "thought leadership" → neutral (references/)
Third sub-pass of the S29 plugin-wide terminology scrub: the banned brand phrase
"thought leadership" (FORM A) removed from the reference-doc surface — the largest pass
(2x S29a/S29b). 34 edits across 15 reference files. Vocabulary consistent with S29a/S29b:
"thought leadership angle(s)" -> "content angle(s)"; "thought leadership" (positioning/practice)
-> "authority ..."; content-type labels -> "authority content / authority posts"; the whole
"Value Test" family -> "Authority Value Test".

Established cross-pass equivalents closed: glossary:229 "Thought Leadership Value Test" ->
"Authority Value Test" (closes the S29b cross-directory naming gap); glossary:29 "8 universal
thought leadership angles" -> "content angles"; engagement-frameworks:137 "Standard Thought
Leadership Structure" -> "Standard Post Structure" (matches S29a post:98).

S29e filename locked this session: thought-leadership-angles.md -> content-angles.md (operator-
chosen). The canonical file's in-file title/headers scrubbed now for consistency (H1 ->
"# Content Angles"; "## The Authority Value Test"; "### Step 3: Test For Authority Value");
the file rename + all 20 pointers remain S29e (atomic).

Judgment-calls (operator-approved): thought-leadership-angles:212 "disguised as thought
leadership" -> "expertise" (S29b vocab); linkedin-formats:295 -> "Text-based content" (avoids
authority...authority echo); linkedin-visual-style:3 -> "For building authority,"; ai-content-
framework:380 "main LinkedIn thought leadership skill" -> "content skill" (avoids awkward
"authority skill"). Kept by design: video-strategy-guide:429 ironic quote; video-strategy-
guide:532 "TL;DW" false positive (too long, didn't watch).

Scope (operator-locked, inherits S29a/S29b): FORM A only. FORM B ("thought leader(s)" as role,
references = 4) untouched. The 3 thought-leadership-angles.md filename pointers in references/
deferred to S29e.

Verify: FORM A in references/ = only the kept ironic quote (video:429); canonical file in-file
FORM A = NONE; FORM B unchanged (4); filename pointers unchanged (3); no anchor links to changed
headers; gate 81/0/0; counts 29/19/26/6 + v0.5.0 unchanged.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_016qgzo6rxthw7KuxHjn5vyE
2026-06-20 05:44:05 +02:00
0e4466b893 fix(linkedin-studio): S9 — full algorithm-magnitude sweep + lint rebuilt to the criterion
Closes the S8 re-review (BLOCK 3/4/1). The S8 fix patched only the 2 strings S7 named; the re-review found 6 more same-class survivors. Per the systemic read, this is a comprehensive sweep, not a per-line patch.

Reconciled every retired engagement-coefficient + model-fact survivor against the canonical references/algorithm-signals-reference.md (order, not coefficients; comment ≈ 2x a like; no model name/params):
- glossary.md: coefficient table + Save-Signal '10x weight' → canonical ordering (citation now true)
- engagement-frameworks.md, analytics-interpreter.md, content-optimizer.md, pipeline.md, engagement-coach.md: the 10x/8x/7-9x/2.5x/0.2x system (incl. 4 survivors the re-review did not cite) → ordering
- playbook: '15x more algorithmic boost' + video '5x more conversations' → directional, sourced
- profile.md + linkedin-voice/SKILL.md: '150B parameter foundation model' → '2026 relevance-ranking model'
- quality-scorecard.md: '360Brew Validation' → topic-relevance framing
- setup.md: 'thought leadership plugin' → 'LinkedIn Studio plugin'

Lint (MAJOR 4): rebuilt scripts/test-runner.sh STALE_STATS to forbid EVERY retired-class phrasing (not the 2 S7 strings) + widened scope to assets/checklists/. Targets retired phrasings (7-9x, (10x), '10x weight', '5x more conversations'), NOT bare 10x/15x/5x (legit 5x5x5 / cadence / pixel-dims / '10x your reach' hyperbole). Proven non-vacuous: catches all 10 retired strings, ignores all 10 legit uses.

Tests (MAJOR 7): added no-anchor fall-through tests for recordFirstHourPlan + recordOutreachContact (date scalar not written/reported, section still appended). MINOR 8: reflowed newsletter.md content-repurposer wiring onto one line.

test-runner.sh 66/0/0; node --test 94/94 (was 92, +2). NO push until /trekreview re-clears the gate.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-05-30 09:56:49 +02:00
Kjell Tore Guttormsen
40986575b6 feat(ultraplan-local): v1.6.0 — /ultraresearch-local deep research command
Add /ultraresearch-local for structured research combining local codebase
analysis with external knowledge via parallel agent swarms. Produces research
briefs with triangulation, confidence ratings, and source quality assessment.

New command: /ultraresearch-local with modes --quick, --local, --external, --fg.
New agents: research-orchestrator (opus), docs-researcher, community-researcher,
security-researcher, contrarian-researcher, gemini-bridge (all sonnet).
New template: research-brief-template.md.

Integration: --research flag in /ultraplan-local accepts pre-built research
briefs (up to 3), enriches the interview and exploration phases. Planning
orchestrator cross-references brief findings during synthesis.

Design principle: Context Engineering — right information to right agent at
right time. Research briefs are structured artifacts in the pipeline:
ultraresearch → brief → ultraplan --research → plan → ultraexecute.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-08 08:58:35 +02:00