Results for “habit-tracking”

Tracks Claude Code tool usage and prompts via hooks to analyze patterns and suggest new skills for repetitive tasks.

Track and visualize ML training experiments with Trackio, including logging metrics, firing alerts, and retrieving data via CLI. Supports real-time dashboards, webhook alerts, and HF Space syncing.

Track elapsed time from a set epoch with tamper-evident locking, supporting count-up, count-down, and count-between modes, milestones, and email notifications.

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.

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

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.

Track ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model registry with W&B.

Detect anomalous user activities including impossible travel, unusual access patterns, privilege abuse, and insider threats using SIEM-based behavioral baselines and statistical analysis.

When the user wants to set up, improve, or audit analytics tracking and measurement. Also use when the user mentions "set up tracking," "GA4," "Google Analytics," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "analytics implementation," "tracking plan," "how do I measure this," "track conversions," "Mixpanel," "Segment," "are my events firing," or "analytics isn't working." Use this whenever someone asks how to know if something is working or wants to measure marketing results. For choosing attribution models, comparing multi-touch/MMM/incrementality, or reconciling conflicting numbers across tools, see attribution. For A/B test measurement, see ab-testing.

Track, analyze, and manage music and audio files from the command line. Use when organizing playlists, converting formats, or analyzing metadata.

Design privacy-aware observability for AI agents using traces, spans, structured events, metrics, cost attribution, dashboards, alerts, and investigation workflows. Use when instrumenting an agent, debugging intermittent tool or model failures, defining service-level objectives, analyzing latency or spend, auditing agent decisions, or preparing production monitoring.

Persistent TODO scratch pad for tracking tasks across sessions. Use when user says "add to TODO", "what's on the TODO", "mark X done", "show TODO list", "remove from TODO", or asks about pending tasks. Also triggers on heartbeat to remind about stale items.

Analyzing session replays, extracting persona-based behavioral patterns, and storytelling UX issues. Reads the 'why' from real user operation logs. Works with Field/Echo for persona validation.

Tracks team OKRs with quarter banner, objective columns, key result progress bars, owner avatars, and status pills.

Track food and nutrition. Use when logging meals, checking calories, tracking protein/carbs/fat, or generating diet reports.

Implement AI chatbot analytics and conversation monitoring. Use when adding conversation metrics, tracking AI usage, measuring user engagement with chat, or building conversation dashboards. Activates for AI analytics, token tracking, conversation categorization, and chat performance.

Diagnose and fix retention problems using the Fogg Behavior Model (B=MAP), covering motivation, ability, prompts, and tiny habits.

Progress Tracking

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.

The practice of collecting, analyzing, and acting on data to drive product decisions. Great analytics isn't about dashboards—it's about insights that lead to action. Every metric should answer a question that changes behavior. This skill covers event tracking, metrics design, dashboards, user behavior analysis, and data-driven decision making. The best analytics teams measure what matters, not what's easy to measure. Use when "analytics, metrics, tracking, dashboard, funnel, cohort, retention, events, KPI, measure, data, insights, conversion, engagement, analytics, metrics, data, dashboards, tracking, funnels, cohorts, KPIs, insights" mentioned.

Set up and track KPI dashboards with targets, actuals, and trend analysis. TRIGGERS - Use when user wants to define KPIs, track metrics, or create a scorecard.

Track ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model registry with W&B - collaborative MLOps platform

Trigger: PostHog event, Segment schema, event properties, user funnel track, track taxonomy. Scope: Product behavioral telemetry, user funnel event models. Boundary: Excludes system performance exceptions.

Set up and track KPI dashboards with targets, actuals, and trend analysis. TRIGGERS - Use when user wants to define KPIs, track metrics, or create a scorecard.

Track ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model registry with W&B - collaborative MLOps platform

Implements user analytics and event tracking in Flutter apps using Firebase Analytics, Mixpanel, and Amplitude, including event definitions, user properties, and e-commerce events.

Generates a compact HTML KPI digest from Adobe Analytics, showing how key metrics changed over a period and what drove the movement.

Debug agent execution by querying trace and metric tables, analyzing tool calls, durations, errors, and performance trends.

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Track ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model registry with W&B - collaborative MLOps platform

Tracks crypto and AI narratives with mindshare scores, velocity arrows, phase labels, named drivers, and position calls. Detects phase transitions and reflexivity signals.

Detects anomalous authentication patterns using UEBA analytics, statistical baselines, and machine learning to identify impossible travel, credential stuffing, brute force, password spraying, and compromised account behaviors across authentication logs.

Performance regression detection using the browse daemon. Establishes baselines for page load times, Core Web Vitals, and resource sizes. Compares before/after on every PR. Tracks performance trends over time. Use when: "performance", "benchmark", "page speed", "lighthouse", "web vitals", "bundle size", "load time". (gstack) Voice triggers (speech-to-text aliases): "speed test", "check performance".

从本地成本追踪数据库追踪并报告 Claude Code 的 Token 用量、花费与预算

Track stocks, ETFs, indices, crypto (where available), and FX pairs with caching + provider fallbacks.