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fix(linkedin-studio): propagate reconciled algorithm numbers, cite-not-restate

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Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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Kjell Tore Guttormsen 2026-05-29 20:32:17 +02:00
commit 4700248cc4
32 changed files with 133 additions and 113 deletions
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plugins/linkedin-studio/references/glossary.md
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@ -6,7 +6,7 @@ Alphabetical glossary of specialized terminology used across the plugin. Each te
## 3
### 360Brew
### Profile/topic relevance
LinkedIn's 150-parameter foundation model that validates creator profiles before distributing content. Checks expertise alignment across About section, Experience, content history, network quality, and engagement patterns. Content from unvalidated profiles receives limited distribution.
**Used in:** `references/algorithm-signals-reference.md`, `skills/linkedin-studio/SKILL.md`, `agents/content-optimizer.md`
@ -21,7 +21,7 @@ Engagement priming technique performed 15-20 minutes before posting: identify 5
## A
### Algorithm Penalty
Negative signal triggers that reduce post reach. Known penalties: 5+ hashtags (-68%), external links in body (-25-40%), off-topic posts (-40-60%), engagement bait phrases (-30-50%).
Signal triggers that correlate with lower reach: excessive hashtags, external links in the post body, off-topic posts (weak profile/topic alignment), and engagement-bait phrases. Magnitudes are directional — see `references/algorithm-signals-reference.md`.
**Used in:** `references/algorithm-signals-reference.md`, `references/linkedin-formats.md`
@ -31,7 +31,7 @@ Systematic application of 8 universal thought leadership angles across the same
**Used in:** `references/thought-leadership-angles.md`, `agents/content-planner.md`, `agents/trend-spotter.md`
### Authority Score
Composite metric measuring a creator's established expertise on a topic, derived from posting consistency, engagement quality, profile alignment (360Brew), and network validation. Higher authority unlocks broader distribution.
Composite metric measuring a creator's established expertise on a topic, derived from posting consistency, engagement quality, profile alignment (topic-relevance), and network validation. Higher authority unlocks broader distribution.
**Used in:** `commands/strategy.md` (authority building absorbed in v2.0.0), `references/algorithm-signals-reference.md`
@ -65,7 +65,7 @@ Optimal content type distribution: 70% Educational (teach, frameworks, how-to),
**Used in:** `skills/linkedin-studio/SKILL.md`, `agents/content-planner.md`, `references/linkedin-growth-playbook-2025-2026.md`
### Content Pillars
3-5 core expertise areas that define your LinkedIn focus. Used for topic consistency validation, gap analysis in content planning, and 360Brew alignment checks. Example for AI content: News, Implementation, Strategy, Tools.
3-5 core expertise areas that define your LinkedIn focus. Used for topic consistency validation, gap analysis in content planning, and topic-relevance alignment checks. Example for AI content: News, Implementation, Strategy, Tools.
**Used in:** `agents/content-planner.md`, `references/ai-content-framework.md`, `skills/linkedin-studio/SKILL.md`
@ -113,7 +113,7 @@ Posts maintaining relevance and engagement potential beyond the initial publicat
**Used in:** `agents/content-repurposer.md`, `references/articles-strategy-guide.md`
### Expertise Verification System
LinkedIn's mechanism for validating creator authority: professional history, posting consistency on specific topics, relevant engagement, domain vocabulary usage, and performance track record. Feeds into 360Brew.
LinkedIn's mechanism for validating creator authority: professional history, posting consistency on specific topics, relevant engagement, domain vocabulary usage, and performance track record. Feeds into topic-relevance.
**Used in:** `references/linkedin-growth-playbook-2025-2026.md`
@ -127,7 +127,7 @@ Critical window (0-60 minutes post-publication) determining ~70% of a post's tot
**Used in:** `skills/linkedin-studio/SKILL.md`, `references/linkedin-formats.md`, `agents/engagement-coach.md`
### Four-Stage Distribution Model
Sequential post distribution: Stage 1 (0-30s: Quality classifier + 360Brew validation) → Stage 2 (0-90min: Test to 6-10% of connections) → Stage 3 (1-24h: Extended if velocity good) → Stage 4 (24-72h+: Evergreen circulation).
Sequential post distribution: Stage 1 (0-30s: Quality classifier + profile/topic-relevance validation) → Stage 2 (0-90min: Test to 6-10% of connections) → Stage 3 (1-24h: Extended if velocity good) → Stage 4 (24-72h+: Evergreen circulation).
**Used in:** `references/algorithm-signals-reference.md`
@ -168,7 +168,7 @@ LinkedIn's feature (2025-2026) measuring user interest in specific topics indepe
## L
### Link Penalty
Algorithm penalty of -25-40% reach for external links placed in the post body. LinkedIn prioritizes keeping users on-platform. Workaround: place links in the first comment instead, or use native document format.
External links in the post body correlate with lower reach (correlational, ~38% in 2026; LinkedIn denies an intentional penalty — see `references/algorithm-signals-reference.md`). Lead with standalone value; a first comment is a hedge, not a fix, and native document format is the durable answer.
**Used in:** `references/algorithm-signals-reference.md`, `references/first-comment-strategy.md`
@ -249,3 +249,4 @@ Deviation from established personal voice profile. Measured across 6 dimensions:
Quantified signature of a creator's unique writing style across sentence structure, vocabulary, hook preferences, storytelling approach, tone, and formatting. Updated quarterly. Identity-level traits (avoided words, tone, humor) are protected from automatic modification.
**Used in:** `agents/voice-trainer.md`, `assets/voice-samples/authentic-voice-samples.md`