# Homunculus Evolution Configuration
#
# Controls how deeply and frequently your AI assistant evolves.
# Edit this file to match your budget and preferences.
#
# `homunculus/budget-profile.json` contains the subscription quota guardrails.
# `evolution-config.yaml` controls which phases are worth spending that quota on.
#
# Tiers:
#   minimal  — Instinct harvest + sync only. Cheapest option. (~$0.5/night)
#   standard — + research + experiments. Good balance. (~$2-3/night) [default]
#   full     — + deeper research + bonus loop. For power users. (~$5-10/night)
#
# Subscription guidance:
#   pro     ($20):  use tier:minimal, research:false, experiments:false
#   max5x   ($100): use tier:standard, 1-2 research topics, 1 experiment
#   max20x ($200): use tier:full, bounded bonus loop and parallel agents
#   api:           use tier:standard/full plus an external spend cap
#
# Dollar cost is optional. Subscription users should primarily track 5h session
# utilization and weekly utilization.

tier: standard  # minimal | standard | full

schedule:
  daily:
    instinct_harvest: true       # Always on — extract patterns from your usage
    instinct_routing: true       # Route high-confidence instincts to implementations
    skill_eval_on_change: true   # Eval only skills that changed today
    health_check_basic: true     # Quick check: hooks working, CLAUDE.md ok
    research: true               # Scan sources for improvements (minimal: false)
    experiments: true            # Run queued experiments (minimal: false)
    bonus_loop: false            # Extra research/experiment rounds until budget runs out
    sync: true                   # Always on — sync CLAUDE.md, memory, architecture
  weekly:
    day: 0                       # 0=Sun, 1=Mon, ..., 6=Sat; -1=run weekly tasks every day
    goal_tree_review: true       # Review all goals for better implementation methods
    full_skill_reeval: true      # Re-evaluate ALL skills (not just changed ones)
    deep_health_check: true      # Full mechanism health check + orphan scan
    autoresearch_boost: true     # Improve eval discrimination score

# Research & experiment counts
# Tier defaults when not specified: minimal=0/0, standard=2/1, full=3-5/3
research:
  topics_min: 2
  topics_max: 2
  dedup_days: 7

experiments:
  max_per_night: 1
  max_half_budget: 1

# Bonus loop settings (only applies when bonus_loop: true)
bonus:
  max_rounds: 5
  cutoff_hour: 5
  cutoff_minute: 30
  max_idle: 2