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>

plugins/linkedin-thought-leadership/references/algorithm-signals-reference.md

@@ -1,4 +1,4 @@
-# LinkedIn Algorithm Signals Reference (January 2026)
+# LinkedIn Algorithm Signals Reference (April 2026)
 
 Quick reference for ranking signals, weights, and penalties. For detailed context, see SKILL.md.
 
@@ -28,6 +28,7 @@ Quick reference for ranking signals, weights, and penalties. For detailed contex
 
 | Signal | Weight | Notes |
 |--------|--------|-------|
+| Delayed engagement (24-72h) | 4-6x boost | Algorithm resurfaces quality content days after publication |
 | Profile views from post | +10-15% | Interest signal, potential follower conversion |
 | Click "see more" | +5-10% | Hook worked, engagement signal |
 | Reactions (all types) | 0.2x | 5x less valuable than comments |
@@ -38,7 +39,9 @@ Quick reference for ranking signals, weights, and penalties. For detailed contex
 | Signal | Penalty | Notes |
 |--------|---------|-------|
 | 5+ hashtags | -68% | Spam signal, triggers AI classifier |
-| AI-generated comments | -30% reach, -55% engagement | Detected and penalized - use human comments only |
+| AI-generated comments | -30% reach, -55% engagement | Detected and penalized — use human comments only |
+| Engagement pods | Shadow-ban | LinkedIn VP: goal to make pods "entirely ineffective". Comment velocity + account relationship analysis active |
+| Third-party script comments | Removed | Comments via automation tools removed from "Most Relevant" feed |
 | Off-topic for profile | -40-60% | 360Brew failure - profile doesn't validate expertise |
 | External link in body | -25-40% | Platform retention focus - use first comment instead |
 | Engagement bait phrases | -30-50% | "Comment YES if...", "Tag someone who...", "Type 1 for..." |
@@ -66,10 +69,10 @@ Quick reference for ranking signals, weights, and penalties. For detailed contex
 
 | Format | Reach Multiplier | Engagement Rate | Best For |
 |--------|------------------|-----------------|----------|
-| PDF/Carousel | 1.6x reach | 24.42% engagement | Frameworks, guides, step-by-step. 12 slides optimal, 25-50 words/slide |
+| PDF/Carousel | 3.4x reach | 1.92% engagement | Frameworks, guides, step-by-step. 7 slides optimal (5-10 range), 25-50 words/slide. 35% click-through minimum or penalty |
 | Multi-image | 1.3x reach | 6.60% engagement | Before/after, comparisons, processes. Best for 5K-10K follower accounts |
 | Polls | 1.64x reach (declining) | 1.5-2% | Audience research only. Declining effectiveness in 2026 |
-| Video (90s) | 1.4x reach | Variable | Personal connection. Always add captions (85% watch muted) |
+| Video (60s) | 1.4x reach | Variable | Personal connection. Vertical 9:16 gets distribution boost. 30% completion rate minimum or zero reach. Always add captions (85% watch muted) |
 | Text-only | 1.17x reach | 3-5% | Thought leadership, stories, opinions. Generates best comment quality |
 | Link posts | -25-40% | <1% | Avoid if possible. Use first comment for links |
 
@@ -80,13 +83,27 @@ Quick reference for ranking signals, weights, and penalties. For detailed contex
 | Post length | 1,200-1,800 chars | <1,000 (-25%) or >2,500 (-32%) |
 | Hook length | <140 chars | >140 truncated on mobile "see more" |
 | Hashtags | 3-4 | 5+ triggers -68% penalty |
-| Video length | 90 seconds | <30s low dwell, >3min high drop-off |
+| Video length | 60 seconds | <30s low dwell, >90s retention drops. 30% completion gate |
 | Posting frequency | 3-5x/week | <2x loses consistency, >2x/day can fatigue |
-| Carousel slides | 12 slides | <8 too short, >15 completion drops |
+| Carousel slides | 7 slides | <5 too short, >10 diminishing returns, >15 completion drops 40% |
 | Caption (carousel) | <500 chars | Focus attention on slides |
 | About section | 2,600 chars | Use all available space, front-load keywords |
 | Headline | 220 chars | Include target audience + outcome |
 
+## 2026 Reach Context
+
+Overall organic reach declined significantly in 2026. This affects everyone — focus on relative performance (your posts vs your baseline), not absolute numbers.
+
+| Metric | Change | Notes |
+|--------|--------|-------|
+| Total reach | -47% YoY | Platform-wide decline |
+| Video content | -72% YoY | Poor video penalized harder, good video still rewarded |
+| Text posts | -34% YoY | Most resilient format |
+| Company pages | ~1.6% of followers | Personal profiles outperform company pages 8x |
+| Posting cadence | 2-5x/week | Sweet spot unchanged despite reach decline |
+
+**Implication:** The algorithm rewards precision over broadcast. Smaller, engaged audiences outperform large but passive ones. 1:1 connections are now more valuable than follower count.
+
 ## Posting Time Windows (CET/European Audience)
 
 | Day | Peak Time | Notes |
@@ -112,10 +129,28 @@ Quick reference for ranking signals, weights, and penalties. For detailed contex
 | 1. Quality Classifier | 0-30s | AI spam/quality check + 360Brew profile validation | Ensure profile matches post topic |
 | 2. Initial Test | 0-90min | 6-10% of connections see post | Stay active, respond to all comments |
 | 3. Extended Distribution | 1-24h | 2nd/3rd degree if velocity good | Continue engagement, add value in comments |
-| 4. Long-tail | 24-72h+ | Evergreen circulation, search/recommendations | Let compound effects work |
+| 4. Long-tail | 24-72h+ | Evergreen circulation. Delayed engagement now yields 4-6x better performance. Algorithm resurfaces high-quality older content | Let compound effects work — high-dwell posts stay active up to 7 days |
 
 **Stage 2 threshold:** 15+ engagements in first hour = unlock Stage 3.
 
+## Depth Score (2026)
+
+LinkedIn's primary content ranking metric. Measures actual engagement duration, not surface interactions. The feed now uses LLM-generated embeddings and transformer-based Generative Recommender models for semantic relevance scoring.
+
+| Factor | Impact | Notes |
+|--------|--------|-------|
+| Time spent reading/watching | Primary signal | Replaced likes as #1 ranking factor |
+| Slide completion (carousel) | High | Each slide click = engagement signal. 7 slides optimal for completion |
+| Video watch percentage | High | 30% minimum completion or zero distribution |
+| Scroll-back behavior | Medium | Re-reading = strong quality signal |
+| Save after reading | Highest | Save + high dwell = maximum distribution boost |
+
+**Distribution impact:**
+- High-dwell posts: active in feeds up to **7 days**
+- Low-dwell posts: dead after **24 hours**
+- First-hour dwell time determines post lifecycle
+- Minimalist carousel design: +12% completion rate vs complex backgrounds
+
 ## 360Brew Profile Validation (January 2026)
 
 **The algorithm validates your profile BEFORE distributing content.**
@@ -124,7 +159,7 @@ Quick reference for ranking signals, weights, and penalties. For detailed contex
 |---------------------|----------------|----------------|
 | About Section | Specific expertise claims, domain terminology | Rewrite with concrete expertise statements |
 | Experience Section | Impact statements with metrics | Add quantified achievements |
-| Content History | Previous posts on this topic, anecdotal evidence | Build topic consistency over 90+ days |
+| Content History | Previous posts on this topic, anecdotal evidence | Requires 90 days of aligned posting for full expertise categorization. Topic mismatch limits reach directly |
 | Network Quality | Connected to professionals in your field | Connect with relevant domain experts |
 | Engagement Patterns | Do you comment on posts in your expertise area? | Daily: 3-5 thoughtful comments in your domain |
 
@@ -165,17 +200,17 @@ Quick reference for ranking signals, weights, and penalties. For detailed contex
 
 ## Red Flags to Avoid
 
-- Engagement pods (actively detected, shadow-ban risk)
+- Engagement pods (LinkedIn VP: goal to make pods "entirely ineffective" — comment velocity analysis and account relationship patterns actively detect manufactured engagement)
 - Pitch-slapping in DMs
 - Posting same content as company page
 - Random topics outside demonstrated expertise
-- "Great post!" style generic comments
+- "Great post!" style generic comments (harm reach even without pod involvement)
 - Excessive self-promotion (>20% of content)
 - Tagging unrelated people for reach
 - Using AI-generated comments (55% engagement penalty)
 
 ---
 
-*Last updated: January 2026*
+*Last updated: April 2026*
 
-*Sources: Research synthesis from Richard van der Blom (Algorithm Research 2025), Lara Acosta (SLAY Framework), 360Brew algorithm analysis, LinkedIn Engineering Blog, Buffer (2M+ post analysis), Sprout Social (2.5B engagements), Justin Welsh, Jasmin Alic, Sahil Bloom case studies*
+*Sources: Research synthesis from Richard van der Blom (Algorithm Research 2025), Lara Acosta (SLAY Framework), 360Brew algorithm analysis, LinkedIn Engineering Blog, Buffer (2M+ post analysis), Sprout Social (2.5B engagements), Justin Welsh, Jasmin Alic, Sahil Bloom case studies. April 2026 update: ALM Corp (LLM architecture analysis), Botdog (360Brew deep dive), DesignACE (engagement signal weights), ContentIn (format strategy guide), UseVisuals (carousel statistics 2026), Visla (video format 2026)*