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Kjell Tore Guttormsen 4dc868ea62 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
..
ab-tests feat(ultraplan-local): v1.6.0 — /ultraresearch-local deep research command 2026-04-08 08:58:35 +02:00
README.md feat(ultraplan-local): v1.6.0 — /ultraresearch-local deep research command 2026-04-08 08:58:35 +02:00

README.md

LinkedIn Analytics Data

This directory contains imported analytics data from LinkedIn CSV exports.

How to Import

  1. Go to LinkedIn Creator Analytics
  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:

{
  "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:

# 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.