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>

assets/analytics/README.md

@@ -0,0 +1,78 @@
+# LinkedIn Analytics Data
+
+This directory contains imported analytics data from LinkedIn CSV exports.
+
+## How to Import
+
+1. Go to [LinkedIn Creator Analytics](https://www.linkedin.com/analytics/creator/content/)
+2. Click **Export** to download a CSV of your content analytics
+3. Save the CSV file to `exports/` directory
+4. Run `/linkedin:import` in Claude Code
+
+## Directory Structure
+
+```
+analytics/
+├── exports/           # Place LinkedIn CSV exports here
+├── posts/             # Auto-generated: imported post data (JSON)
+├── weekly-reports/    # Auto-generated: weekly performance reports (JSON)
+└── README.md          # This file
+```
+
+## Data Format
+
+### Post Analytics (posts/*.json)
+
+Each file contains a batch of imported posts:
+
+```json
+{
+  "batchId": "batch-...",
+  "importedAt": "2026-01-29T...",
+  "exportFilename": "content-analytics.csv",
+  "dateRange": { "from": "2026-01-13", "to": "2026-01-28" },
+  "postCount": 8,
+  "posts": [
+    {
+      "id": "abc123",
+      "title": "First 100 chars of post...",
+      "publishedDate": "2026-01-28",
+      "metrics": {
+        "impressions": 4523,
+        "reactions": 87,
+        "comments": 23,
+        "shares": 12,
+        "clicks": 156,
+        "engagementRate": 6.15
+      }
+    }
+  ]
+}
+```
+
+### Weekly Reports (weekly-reports/*.json)
+
+Generated via `/linkedin:report`. Contains:
+- Summary metrics (totals, averages)
+- Top and underperforming posts
+- Week-over-week trends
+- Performance alerts (spikes, drops)
+
+## CLI Usage
+
+The analytics CLI can also be invoked directly:
+
+```bash
+# Import a CSV export
+ANALYTICS_ROOT=./assets/analytics node --import tsx scripts/analytics/src/cli.ts import <filename>
+
+# Generate weekly report
+ANALYTICS_ROOT=./assets/analytics node --import tsx scripts/analytics/src/cli.ts report --week 2026-W05
+
+# Analyze trends
+ANALYTICS_ROOT=./assets/analytics node --import tsx scripts/analytics/src/cli.ts trends --period month --metric impressions
+```
+
+## Privacy
+
+All data in this directory (except this README) is gitignored. Your analytics data stays local.