# 2026-03-05

## Council skill created and iterated
- Built `skills/council/` — multi-perspective advisory council using subagents.
- Design decisions (agreed with Will):
  - Implemented as a **skill** (not standalone agents).
  - 3 advisors (Pragmatist, Visionary, Skeptic) + 1 Referee = 4 subagents total.
  - Referee is a separate subagent (not the session model) — can use a stronger model tier.
  - Default flow: **Parallel + Synthesis**. Sequential and Debate flows also available.
  - Final output includes individual advisor perspectives (collapsed/summarized) + referee verdict.
  - Model tier chosen per-invocation based on topic complexity.
- Two live tests run:
  - Test 1: Parallel single-round on "Do LLM agents think?" — worked well.
  - Test 2: Parallel 3-round debate on same topic — richer output, positions evolved meaningfully across rounds.
- Post-test iteration: updated skill with configurable parameters:
  - `flow` (parallel/sequential/debate), `rounds` (1-5), `tier` (light/medium/heavy)
  - Round-specific prompt templates (opening, rebuttal, final position)
  - Multi-round referee template that tracks position evolution
  - Word count guidance that decreases per round to control token cost
  - Subagent labeling convention: `council-r{round}-{role}`
- Files: `SKILL.md`, `references/prompts.md`, `scripts/council.sh` (reference doc).
- TODOs in `memory/tasks.json`:
  - Revisit advisor personality depth (richer backstories).
  - Revisit skill name ("council" is placeholder).
  - Experiment with different round counts and flows for optimal depth/cost tradeoffs.