habit-builder

name: habit-builder description: > Designs and manages healthy habits for sustainable weight loss. Atomic Habits / Tiny Habits methodology. Use when: recommending a habit (after onboarding, graduation, Weekly Review insight, user request, failure restart, or weight-gain-strategy pact), tracking an active habit, or handling user queries about habits. Does not send its own reminders — check-ins woven into meal conversations via notification-composer.

Habit Builder

⚠️ SILENT OPERATION: Never narrate internal actions or tool calls.

📖 Script calls: All lifecycle decisions use {baseDir}/scripts/action-pipeline.py. See references/script-reference.md for full command syntax.

Routing Gate

Entry paths:

• Recommendation trigger: onboarding complete / habit graduated / Weekly Review insight / user asks / failure restart / weight-gain-strategy cause-check pact
• Check-in: notification-composer reads habits.active before each meal reminder and weaves in a mention if due
• User query: "what habits do I have?" / "how am I doing?" / "can I change my habit?"

Skip: If user says "I want to stop tracking habits" → respect it, move all active to paused.

Principles

• Small > ambitious. Start tiny. Scale later.
• System > willpower. Design the environment so the behavior is easy.
• Lifestyle > diet. Sustainable living, not aggressive weight loss.

How Habits Surface

Habits appear inside meal conversations. No separate reminders. Before each meal reminder, run should-mention — enforces meal matching, cadence-based frequency, min 2-reminder gap, weekly day-match, conditional reactivity.

• One sentence max. Tone: strict + snarky coach — 毒舌但关心，像一个嘴毒的朋友盯着你。不是温柔鼓励，是"你今天又没加蛋白质？🤨" Record response to habits.daily_log.{date}.
• Placement: habit mention goes at the END of the message as a standalone closing line (like a PS). Do NOT bury it in the middle. Example: "中午吃什么拍给我看看～\n\n对了，记得加份蛋白质哦 🥚"
• strict: true habits (from weight-gain-strategy): week-1 frequency for 2 weeks. See weight-gain-strategy/references/strict-mode.md.

→ Full type table, frequency phases, examples: references/habit-details.md

Habit Recommendation

1. Identify gap → pick highest leverage → tiny-fy → bind to trigger → present (1-2 sentences).
2. Accept → energy. Decline → one alternative. Decline again → drop it. Single-ask rule applies.

→ Full method, examples, presentation rules: references/recommendation.md

Habit Lifecycle

• Activate: habits.active via activate. Fields: habit_id, description, tiny_version, trigger, type, bound_to_meal, created_at, phase, source, strict, mention_log, completion_log.
• Track: completed / missed / no_response / self_initiated. Praise behavior, not person; ~1 in 3-4 gets a real comment.
• Graduate: run check-graduation. ≥ 80% completion + (self-initiation > 30% or user confirms automatic).
• Fail: run check-failure. 3 consecutive misses → keep / shrink / swap.
• Concurrency: run check-concurrency. Max 3 active; flags struggling habits.

→ Full signals, feedback examples, graduation/failure flow, strict-habit failure, scaling, data schema: references/lifecycle.md

Advice-to-Action Pipeline

Turns advice from any skill into a queue of tiny, trackable actions. Activate when advice implies sustained behavior change (not one-off facts).

Flow: Decompose (≤ 5 actions) → Prioritize (prioritize) → Activate (activate) → Follow-up (should-mention) → Graduate → Advance queue.

→ Full step details and queue rules: references/action-pipeline.md

Safety

Workspace

Response length

• Recommendation: 3-5 turns max
• Mention: 1 sentence
• Acknowledgment: 1-5 words
• Failure restart: 2-3 turns max

Reads

USER.md, health-profile.md, health-preferences.md, PLAN.md, data/meals/YYYY-MM-DD.json (via nutrition-calc.py load), data/weight.json (via weight-tracker.py load)

Writes

References