Kjell Tore Guttormsen
853cad3ade
Closes the S9 re-review (1 BLOCKER + 2 MAJOR, all grep-verified). The survivor
set converged 8 -> 6 -> 2; this closes the meta-problem behind the convergence,
not just the two lines.
BLOCKER — references/glossary.md:10: drop the fabricated "150-parameter
foundation model" (a garbled 150B that the S9 enumerative grep/lint, requiring a
"B"/"billion", could not match). Reframe to "a real input to LinkedIn's 2026
relevance-ranking model" with no parameter count, citing
algorithm-signals-reference.md inline — which makes the :12 "Used in" provenance
accurate (the reference does state the relevance-ranking framing; it never stated
"150-parameter").
MAJOR — CHANGELOG.md:308: de-brand "360Brew profile optimization (January 2026
algorithm update)" -> "Profile/topic-relevance optimization". Removes the
unpublishable brand + asserted Jan-2026 date, honouring v4.0.0's "removed
everywhere" claim. It was the only STALE_STATS hit in CHANGELOG.
MAJOR — scripts/test-runner.sh: the rebuilt lint was enumerative on surface form.
Generalize it to the PATTERN CLASS so the same grep that defines the SC fails on
any surface form, present or future:
- STALE_STATS model token: "150 ?B param|150 billion param"
-> "[0-9]+[ -]?(B|billion)?[ -]?param"
(covers 150-parameter / 150B param / 150 billion param). This robustifies the
review's literal suggestion "[0-9]+[ -]?(B|billion )?param", which missed the
space form "150B param"; the separator is moved out of the group.
- STAT_HITS grep scope += CHANGELOG.md (the 360Brew survivor lived outside it).
- Permanent non-vacuity SELF-TEST before the real scan: 13 forbidden probes must
match (incl. the exact "150-parameter" survivor), 8 legitimate probes must not
("Language parameter", "parameterized", "different parameters",
"175-milliarders parametermodell", 5x5x5, cadence, pixel dims, "10x your
reach"). S7->S9 each shipped a green lint because the proof was run by hand and
never committed; this makes narrowing STALE_STATS fail the suite.
Verification: test-runner.sh 67/0/0 exit 0 (was 66/0/0; +1 self-test);
node --test 94/94; broadened exhaustive grep across the tree -> zero survivors.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
252 lines
13 KiB
Markdown
252 lines
13 KiB
Markdown
# LinkedIn Studio Glossary
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Alphabetical glossary of specialized terminology used across the plugin. Each term includes a definition and cross-references to where it's used.
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---
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## 3
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### Profile/topic relevance
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How well a creator's profile and expertise align with the topic they post about — a real input to LinkedIn's 2026 relevance-ranking model that gates distribution. The model checks expertise alignment across the About section, Experience, content history, network quality, and engagement patterns; content from profiles with weak topic alignment receives limited distribution. (The relevance-ranking model's production name and size are not publishable as fact — see `references/algorithm-signals-reference.md`.)
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**Used in:** `references/algorithm-signals-reference.md`, `skills/linkedin-studio/SKILL.md`, `agents/content-optimizer.md`
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### 5x5x5 Pre-Posting Method
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Engagement priming technique performed 15-20 minutes before posting: identify 5 people with overlapping audiences, find their recent posts (last 24h), write 5 thoughtful comments (15+ words each). Primes algorithm visibility and warms engagement signals.
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**Used in:** `skills/linkedin-studio/SKILL.md`, `agents/engagement-coach.md`, `agents/network-builder.md`
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---
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## A
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### Algorithm Penalty
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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`.
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**Used in:** `references/algorithm-signals-reference.md`, `references/linkedin-formats.md`
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### Angle Rotation
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Systematic application of 8 universal thought leadership angles across the same topic to create distinct post variations without repeating yourself. The 8 angles: Contrarian Take, Pattern Recognition, Uncomfortable Truth, Future Implication, Personal Lesson, Reframe, Practical Breakdown, Human Story.
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**Used in:** `references/thought-leadership-angles.md`, `agents/content-planner.md`, `agents/trend-spotter.md`
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### Authority Score
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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.
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**Used in:** `commands/strategy.md` (authority building absorbed in v2.0.0), `references/algorithm-signals-reference.md`
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---
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## C
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### CEA Method (Comment Engagement Architecture)
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Three-step comment quality framework: **C**ompliment (specific point appreciated) → **E**xpand (add your insight or experience) → **A**sk (question to continue dialogue). Minimum 15 words for algorithmic value.
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**Used in:** `agents/engagement-coach.md`, `references/algorithm-signals-reference.md`
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### Commodity Content
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Generic, non-differentiated posts that repeat common advice without original perspective. Detected by the differentiation-checker agent using a 10-item red flag checklist; 3+ flags = commodity. Should be blocked or reworked before publishing.
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**Used in:** `agents/differentiation-checker.md`
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### Content DNA
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Your unique combination of perspective, experience, voice, and topical focus that distinguishes your content from others in the same space. Built through consistent posting on core topics over 90+ days. Synthesized by analytics-interpreter (report mode) as a personal formula.
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**Used in:** `agents/voice-trainer.md`, `agents/differentiation-checker.md`, `agents/analytics-interpreter.md`
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### Content Lifecycle
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Seven-stage journey of repurposed content: Original Creation → First Repurposing → Angle Rotation → Format Variation → Series Expansion → Evergreen Circulation → Archive Review. Managed by the content-repurposer agent.
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**Used in:** `agents/content-repurposer.md`
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### Content Mix (70/20/10)
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Optimal content type distribution: 70% Educational (teach, frameworks, how-to), 20% Inspirational (stories, lessons, failures), 10% Entertaining (hot takes, humor, observations). Enforced by content-planner agent.
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**Used in:** `skills/linkedin-studio/SKILL.md`, `agents/content-planner.md`, `references/linkedin-growth-playbook-2025-2026.md`
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### Content Pillars
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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.
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**Used in:** `agents/content-planner.md`, `references/ai-content-framework.md`, `skills/linkedin-studio/SKILL.md`
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### CTA (Call-to-Action)
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Specific, genuine engagement prompt at the end of a post. Must feel natural and offer optionality ("Which strategy has worked for your team?" > "What do you think?"). Creates invitation for the engagement that drives distribution.
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**Used in:** `references/engagement-frameworks.md`, `skills/linkedin-studio/SKILL.md`, `agents/content-optimizer.md`
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---
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## D
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### Dwell Time
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Duration a user spends viewing content with ≥50% visible on screen. Posts with 30+ seconds dwell time signal quality to the algorithm (+25% boost). Save behavior strongly correlates with high dwell time.
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**Used in:** `references/linkedin-growth-playbook-2025-2026.md`, `references/linkedin-formats.md`
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---
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## E
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### Engagement Bait
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Prohibited engagement tactics ("Comment YES if...", "Tag someone who...", "Type 1 for...") that trigger -30-50% reach penalty. The algorithm actively detects and penalizes these patterns.
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**Used in:** `references/algorithm-signals-reference.md`
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### Engagement Pod
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Coordinated group of accounts that artificially boost each other's posts. Actively detected by LinkedIn; risks shadow-ban and engagement penalty. Warned against in multiple plugin references.
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**Used in:** `references/linkedin-growth-playbook-2025-2026.md`, `commands/outreach.md` (collab absorbed in v2.0.0), `agents/network-builder.md`
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### Engagement Quality Hierarchy
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The defensible **ordering** of engagement signals — **saves > shares > quality comments (15+ words) > reactions/likes** — not a fixed coefficient table (LinkedIn publishes no such weights). Directional single-vendor estimates: a save ≈ 5x a like (≈ 2x a comment); a quality comment ≈ 2x a like. Trust the order, test the number — these are not hard multipliers to optimize against.
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**Used in:** `references/algorithm-signals-reference.md`, `references/engagement-frameworks.md`
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### Engagement Velocity
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Speed of engagement accumulation in the first hour after posting. 15+ engagements in the first hour unlocks Stage 3 distribution. Monitored at 5/15/30/60/90-minute intervals.
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**Used in:** `references/algorithm-signals-reference.md`, `assets/audience-insights/engagement-patterns.md`
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### Evergreen Content
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Posts maintaining relevance and engagement potential beyond the initial publication window. Identified through scoring (topical relevance, performance, refresh potential). Suitable for repurposing over 12+ months.
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**Used in:** `agents/content-repurposer.md`, `references/articles-strategy-guide.md`
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### Expertise Verification System
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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.
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**Used in:** `references/linkedin-growth-playbook-2025-2026.md`
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---
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## F
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### First-Hour Engagement
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Critical window (0-60 minutes post-publication) determining ~70% of a post's total reach. Requires: 5x5x5 pre-posting engagement, immediate response to first comments (within 5 minutes), and continued engagement through 90 minutes.
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**Used in:** `skills/linkedin-studio/SKILL.md`, `references/linkedin-formats.md`, `agents/engagement-coach.md`
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### Four-Stage Distribution Model
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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).
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**Used in:** `references/algorithm-signals-reference.md`
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---
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## G
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### Golden Hour
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The critical 60-90 minute window post-publication where LinkedIn tests content with a small connection sample. Strong performance (1,000+ impressions) unlocks broader distribution; weak performance (<500) limits reach.
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**Used in:** `references/linkedin-growth-playbook-2025-2026.md`
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---
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## H
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### Hook
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Opening 110-140 characters of a post that must work standalone on mobile (before "see more" cutoff) and create a curiosity gap. 10 high-performing types: Surprising Stat, Bold Statement, Provocative Question, Contrarian, Personal Confession, Pattern Observation, Time Frame Urgency, Lesson Learned, Scenario, Direct Address.
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**Used in:** `references/engagement-frameworks.md`, `skills/linkedin-studio/SKILL.md`, `agents/content-optimizer.md`
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### Hook Psychology
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Neuroscience-backed engagement: Pattern interrupts trigger prediction error → dopamine release → information gap demanding cognitive closure. Pattern interrupts are 2.7x more common in viral posts. Optimal first line: ~49 characters.
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**Used in:** `references/engagement-frameworks.md`
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---
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## I
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### Interest Graph
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LinkedIn's feature (2025-2026) measuring user interest in specific topics independent of their connection network. Platform increased outside-network content distribution by 40% when grounded in professional knowledge.
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**Used in:** `references/linkedin-growth-playbook-2025-2026.md`
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---
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## L
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### Link Penalty
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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.
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**Used in:** `references/algorithm-signals-reference.md`, `references/first-comment-strategy.md`
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## N
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### Network Tiers
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Three-level connection classification: **Tier 1** (Inner Circle, 5-10 people, daily engagement), **Tier 2** (Active Network, 2-3x weekly engagement), **Tier 3** (Extended Network, monthly engagement). Used for strategic resource allocation.
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**Used in:** `agents/network-builder.md`, `commands/outreach.md` (collab absorbed in v2.0.0)
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## O
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### Originality Score
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0-100 metric across 5 dimensions: perspective uniqueness, experience authenticity, angle freshness, data/evidence originality, voice distinctiveness. Score 51+ = passable, 66+ = differentiated, 81+ = exceptional. Gate threshold: 51/100 minimum.
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**Used in:** `agents/differentiation-checker.md`
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---
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## P
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### Pattern Interrupt
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Unexpected statement or data point that breaks normal thought patterns and captures attention. 2.7x more common in viral posts. Examples: contrarian claims, surprising statistics, provocative questions.
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**Used in:** `references/engagement-frameworks.md`
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---
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## R
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### Repurposing Priority Score
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0-100 metric evaluating content readiness for format conversion: Performance (40pts), Quality (30pts), Format Fit (30pts). Used to prioritize which content gets repurposed first.
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**Used in:** `agents/content-repurposer.md`
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## S
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### Save Signal
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Highest-value engagement signal — top of the engagement order. A save ≈ 5x a like (≈ 2x a comment) in single-vendor data — directional, not a fixed weight. Saves indicate content worth returning to; posts with saves get 130% higher follow probability. Only ~3% of posts reach save-worthy status.
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**Used in:** `references/algorithm-signals-reference.md`, `references/linkedin-growth-playbook-2025-2026.md`
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### Shadow Ban
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Penalty state where posts reach only immediate connections without algorithmic amplification. Triggered by engagement pods, artificial boosting, or consistent guideline violations. Not officially announced by the platform.
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**Used in:** `references/linkedin-growth-playbook-2025-2026.md`
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---
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## T
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### Thought Leadership Value Test
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Three-question quality gate before publishing: (1) Does this help someone make a better decision? (2) Does this change how someone thinks? (3) Would I find this valuable if someone else wrote it? Must pass all three.
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**Used in:** `references/thought-leadership-angles.md`, `agents/differentiation-checker.md`, `agents/trend-spotter.md`
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### Topical Consistency
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Posting about consistent topics within demonstrated expertise areas. The algorithm learns your domain expertise over 30+ days. Gaps >5 days trigger -15-25% reach penalty on return.
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**Used in:** `references/linkedin-growth-playbook-2025-2026.md`, `references/algorithm-signals-reference.md`
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---
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## V
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### Voice Drift
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Deviation from established personal voice profile. Measured across 6 dimensions: sentence structure, word choice, hooks, storytelling, tone, formatting. Thresholds: 70%+ = AUTHENTIC, 40-69% = CAUTION, <40% = ALERT/REWRITE.
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**Used in:** `agents/voice-trainer.md`
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### Voice Profile
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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.
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**Used in:** `agents/voice-trainer.md`, `assets/voice-samples/authentic-voice-samples.md`
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