linkedin-studio/CONTRIBUTING.md
Kjell Tore Guttormsen 40986575b6 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

1.3 KiB

Contributing to linkedin-thought-leadership

This is a solo project. Bug reports and feature requests are welcome, but pull requests are not accepted.

Reporting bugs

Open an issue with:

  • Plugin version (from .claude-plugin/plugin.json)
  • Claude Code version (claude --version)
  • What you did, what you expected, what happened instead
  • Whether it fails consistently or occasionally

Suggesting features or improvements

Open an issue describing:

  • The problem you ran into
  • What you think would solve it
  • Any alternatives you considered

Design principles

Changes to this plugin must preserve:

  • Cross-platform — all hooks are Node.js (.mjs), no bash dependency
  • Privacy-first — personal data (voice samples, analytics, queue) stays gitignored
  • Generalizable — no hardcoded user identity; templates for personalization
  • Cost-aware — Sonnet for most agents, Haiku for lightweight tasks
  • Algorithm-grounded — content strategies backed by documented LinkedIn signals

Testing locally

claude plugin add /path/to/linkedin-thought-leadership

# In a Claude Code session:
/linkedin           # Check status and command menu
/linkedin:quick     # Test quick post flow
/linkedin:profile   # Test profile audit

For analytics:

cd scripts/analytics && npm install && npm test