Results for “habit-formation”

Design habit-forming product loops using the Hook Model (Trigger, Action, Variable Reward, Investment) to analyze and improve user engagement, retention, and re-engagement strategies.

Design habit-forming product loops using the Hook Model (Trigger, Action, Variable Reward, Investment). Use when the user mentions "users arent coming back", "engagement loops", "habit formation", "push notifications", "variable rewards", "daily active users", "habit zone", or "user retention loops". Also trigger when designing notification strategies, building streaks or progress systems, or analyzing why users stop using a product after initial signup. Covers ethics evaluation and onboarding for habits. For friction reduction and B=MAP, see improve-retention. For viral sharing, see contagious.

当试图建立或改变一个习惯、例行程序，但遇到阻力或难以坚持时

Diagnose and fix retention problems using behavior design (B=MAP). Use when the user mentions "users drop off", "activation rate", "onboarding friction", "retention metrics", "why users dont complete", "churn analysis", "user activation", or "aha moment". Also trigger when analyzing cohort retention curves, designing activation milestones, reducing time-to-value for new users, or investigating why users stop after their first session. Covers the Ability Chain, prompt design, and tiny behaviors that compound. For habit loops and variable rewards, see hooked-ux. For intrinsic motivation, see drive-motivation.

当需要启动一天，建立积极基调并获取初始能量时

Retention and recurring-value design for Nick's products. Use when deciding how users come back, what keeps value recurring, how to reduce churn, and how to create stronger habit or workflow retention.

Turn "they bought it but nobody uses it" into a plan to fix it. Reads what is unused inside an account, picks the one habit to build next, and writes the enablement plan that gets there. Built for B2B customer success teams, customizable to your product and your onboarding. Trigger on "drive adoption", "which features are unused", "why aren't they using it", "seats sitting idle", "build an enablement plan", or any account-adoption diagnostic.

Generates a gamified habit-tracking app UI with three phone frames: a cover poster, today's quests with XP and level bar, and a quest detail view with subtasks and rewards.

Build a weekly cadence of customer touchpoints using Opportunity Solution Trees, assumption mapping, and interview snapshots to keep product decisions grounded in evidence.

当需要建立可持续的创造节奏，将灵感转化为行动时

Analyze user engagement and retention patterns by cohort to identify trends in user behavior, feature adoption, and long-term engagement.

Expert in creating opening lines, thumbnails, and hooks that stop the scroll. Covers curiosity gaps, pattern interrupts, emotional triggers, and platform-specific hooks. Knows how to earn attention in the first 3 seconds without resorting to clickbait. Use when "hook, opening line, scroll stopper, headline, first line, attention grab, thumbnail, clickable, " mentioned.

Enforce idiomatic Rust patterns for ownership, error handling, enums, traits, concurrency, and best practices to build safe, performant applications.

Wrap a learning session in a plan → monitor → reflect cycle. Use at the start of any substantial study session to set goals, mid-session to check strategy, and at session end to consolidate what changed. Builds self-regulated learning as a habit.

Continuous self-improvement through systematic logging, pattern detection, and behavioral updates. Use when: the owner corrects you, a task fails, you discover a better approach, or you notice a recurring pattern. Store raw learnings in .learnings/, update the specific skill or workflow that caused the issue when appropriate, and avoid vague promises to do better.

Build students' capacity to compare accounts across multiple historical sources — identifying agreements, contradictions, and gaps. Use when students treat individual documents as complete answers rather than partial perspectives.

当个体在数字环境中困惑于自身角色（消费vs创造），或认为吸引注意力不道德时

Idiomatic Rust patterns, ownership, error handling, traits, concurrency, and best practices for building safe, performant applications.

日本語の生産性コーチングモード。明示的な依頼、反復失敗、受け身、検証不足、品質不満のときに、構造化トラブルシューティングと証拠ベースの完了確認を促す。

Improves user onboarding and activation by defining the aha moment, designing effective onboarding flows, and building engagement loops to boost retention.

Design a diary study plan with prompts, duration, participant criteria, and analysis framework to understand user behavior over time in natural contexts.

Transform learning content (like YouTube transcripts, articles, tutorials) into actionable implementation plans using the Ship-Learn-Next framework. Use when user wants to turn advice, lessons, or educational content into concrete action steps, reps, or a learning quest.

Stores, retrieves, and curates persistent facts in a structured memory map, distinguishing between user facts and reference text.

Graduate a proven pattern from auto-memory (MEMORY.md) to CLAUDE.md or .claude/rules/ for permanent enforcement.

当意识到当前行为模式可能导致不理想的未来，需要一种具体方法来激发改变动力时

当需要高效掌握新技能并将知识转化为实际成果，避免“纸上谈兵”时

Debugging constant Markov regime features in RL observations - when HMM probabilities show uniform values instead of dynamic regime estimates

Capture and organize general facts about the user by topic, such as preferences, background, and goals, to personalize interactions.

The science of learning through controlled experimentation. A/B testing isn't about picking winners—it's about building a culture of validated learning and reducing the cost of being wrong. This skill covers experiment design, statistical rigor, feature flagging, analysis, and building experimentation into product development. The best experimenters know that every test, positive or negative, teaches something valuable. Use when "a/b test, experiment, hypothesis, statistical significance, sample size, feature flag, variant, control, treatment, p-value, conversion rate, test winner, split test, experimentation, testing, statistics, feature-flags, hypothesis, growth, optimization, learning, validation" mentioned.

Generate retrieval practice questions at varied difficulty levels for a topic or concept. Use when creating quiz starters, revision activities, or low-stakes testing materials.

Design and improve product user onboarding (first-time user experience) to drive activation and early retention. Produces an Onboarding & Activation Pack (aha moment spec, first 30 seconds + first mile plan, onboarding journey map, experiment backlog, measurement plan). Use for Growth teams.

Design MVPs, validated learning experiments, and pivot-or-persevere decisions using the Build-Measure-Learn loop and innovation accounting.

Capture actionable learnings that emerge during conversation — when the agent or user discovers that a skill, a set of skills, or a process needs to be updated based on what's happening in the current chat. Sub-skill of the learn-from orchestrator. Load when the user says "we should update the skill for this", "this should be a skill rule", "add this as a gotcha", "the skill should know about this", "update the process for this", "remember this for next time", "this is important for the skill". Also triggers when the agent notices a skill's guidance was wrong or incomplete, a process step failed or was unnecessary, a new pattern emerged, a guardrail was missing, a workaround became a pattern, or a debugging session reveals a gap.

日本語の生産性コーチングモード。明示的な依頼、反復失敗、受け身、検証不足、品質不満のときに、構造化トラブルシューティングと証拠ベースの完了確認を促す。

週次リフレクション（1週の振り返りサマリ）を生成するスキル。直近の完了週の日記から4要素（作業傾向/思考癖/繰り返す課題/CCアドバイス）を生成し、_INDEX気づきTop3はユーザー承認後に反映。ユーザーが「リフレクション」「今週の振り返り」「思考癖まとめて」と言った時、または /reflection を呼んだ時に発動。resume-sessionの検知提案からも起動される。