Instructions for managing CI pipelines, GitHub Actions workflows, Airflow DAGs, and automation scripts in the insurance analytics project.
日本語の概要は準備中です。原文の説明を表示しています。
983 件 ・ 関連度順
概要と使いどころ
Instructions for managing CI pipelines, GitHub Actions workflows, Airflow DAGs, and automation scripts in the insurance analytics project.
日本語の概要は準備中です。原文の説明を表示しています。
A/B test design — produce an experiment spec with hypothesis, primary metric, MDE, sample size, run time, and decision rule. Also determines when NOT to A/B test and what to do instead. Use when asked to "design an A/B test", "should we test this", "experiment design", "how do we know if this works", "what's the sample size", or "set up an experiment".
日本語の概要は準備中です。原文の説明を表示しています。
Produce a complete metrics definition doc — metric name, formula, data source, segmentation, SQL or event tracking spec, and what good/bad looks like. Given a product area, outputs the full metrics spec. Use when asked to "define KPIs", "metrics framework", "what should we measure", "north star metric", or "instrument this feature".
日本語の概要は準備中です。原文の説明を表示しています。
Build a reporting pipeline — scheduled reports with SQL queries, delivery via Slack or email, threshold alerts, and historical comparison. Use when asked for "automated reports", "scheduled report", "email digest", or "Slack alerts for metrics".
日本語の概要は準備中です。原文の説明を表示しています。
Use when asked to analyze a funnel, find where users drop off, diagnose low conversion or activation rates, design a metrics framework, set up OKRs, or measure whether a feature is working. Examples: "analyze our funnel", "why is activation low", "where are users dropping off", "design OKRs for this quarter", "is this feature working", "set up metrics for this launch".
日本語の概要は準備中です。原文の説明を表示しています。
Product analyst — metrics architecture, funnel analysis, A/B test design, retention, and growth measurement. Use when asked to "design an A/B test", "analyze the funnel", "define a north star metric", or "measure retention".
日本語の概要は準備中です。原文の説明を表示しています。
Metrics architecture — produce a complete metrics plan given a product description. North Star, input metrics tree, instrumentation spec, action triggers, and counter-metrics. Use when asked to "design a metrics framework", "what should we measure", "build a metrics system", "define our KPIs", "what are our success metrics", "metrics strategy", or "what do we track".
日本語の概要は準備中です。原文の説明を表示しています。
User segmentation and persona creation from mixed data sources — analytics, CRM, support tickets, reviews, or any combination. Use when asked to "build personas", "who are our users", "segment our users", "create user profiles", "define user archetypes", or "who is the target user".
日本語の概要は準備中です。原文の説明を表示しています。
Spawn-count analytics for the tonone roster — which agents this project actually uses, from local session transcripts. Use when "which agents do we actually use", "show tonone stats", "prune the roster", or before running apex-profile.
日本語の概要は準備中です。原文の説明を表示しています。
Expert guide for Feature Flags & Progressive Rollout (PostHog, LaunchDarkly, GrowthBook), A/B testing orchestration, and canary releases / Panduan ahli Feature Flags, A/B testing, dan rilis bertahap.
日本語の概要は準備中です。原文の説明を表示しています。
Expert guide for Data Pipelines, ETL/ELT, and Analytics Engineering. Covers dbt, Apache Airflow, Dagster, BigQuery, ClickHouse, and DuckDB / Panduan ahli untuk Data Pipelines, ETL/ELT. Mencakup dbt, Airflow, Dagster, BigQuery, ClickHouse, dan DuckDB.
日本語の概要は準備中です。原文の説明を表示しています。
Expert guide for observability, analytics, telemetry, and data pipelines (OpenTelemetry, PostHog, Mixpanel) / Panduan ahli untuk observabilitas, telemetri, dan analitik.
日本語の概要は準備中です。原文の説明を表示しています。
When the user wants to plan, design, or implement an A/B test or experiment. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," or "hypothesis." For tracking implementation, see analytics-tracking.
日本語の概要は準備中です。原文の説明を表示しています。
Performance measurement, attribution modeling, and marketing ROI analysis. Use when setting up tracking, analyzing campaign performance, building attribution models, or creating marketing reports.
日本語の概要は準備中です。原文の説明を表示しています。
When the user wants to plan, design, or implement an A/B test or experiment. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," or "hypothesis." For tracking implementation, see analytics-tracking.
日本語の概要は準備中です。原文の説明を表示しています。
X/Twitter API integration for posting tweets, threads, reading timelines, search, and analytics. Covers OAuth auth patterns, rate limits, and platform-native content posting. Use when the user wants to interact with X programmatically.
日本語の概要は準備中です。原文の説明を表示しています。
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
日本語の概要は準備中です。原文の説明を表示しています。
Complete DataForSEO API integration for SEO data and analysis. Use when the user asks for keyword research, search volume, SERP analysis, backlink audits, competitor analysis, rank tracking, domain authority, technical SEO audits, content monitoring, Google Trends, or any SEO-related data queries. Covers all DataForSEO APIs including SERP, Keywords Data, DataForSEO Labs, Backlinks, OnPage, Domain Analytics, Content Analysis, Business Data, Merchant, App Data, and AI Optimization APIs. Outputs CSV files.
日本語の概要は準備中です。原文の説明を表示しています。
Use for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability, error tracking, product analytics warehouse) in parallel, then returns a cited read on decisions and tradeoffs. Use how for runtime behavior.
日本語の概要は準備中です。原文の説明を表示しています。
Build MotherDuck analytics into customer-facing applications with tenant isolation, backend routing, and serving APIs.
日本語の概要は準備中です。原文の説明を表示しています。
Use whenever the user wants to find, shortlist, vet, or enrich US AI/ML/data consulting firms (consultancies) — AI/ML development, MLOps, generative AI / LLM apps (RAG, chatbots, agents), computer vision, NLP, recommendation systems, data engineering, BI/analytics. Triggers on "find an AI/ML consulting firm to build our recommendation engine", "shortlist three RAG/LLM consultancies for an enterprise chatbot", "compare three AI/ML consulting firms with strong ratings", or "pull contact info for these 8 AI consultancy domains", even when described indirectly (we want to use AI for X, deploy ML to production). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Defer to find-software-developer for general app/backend work where AI is just a feature. Skip in-house ML/data hires, LLM/AI-tool comparisons (ChatGPT vs Claude), "how do I fine-tune X" DIY questions, AI courses for individuals, non-US firms, individual freelancers.
日本語の概要は準備中です。原文の説明を表示しています。
YouTube Marketing MCP — 21-command suite for YouTube creators. Covers SEO, scripts, hooks, thumbnails, analytics, content calendar, Shorts, batch updates, WordPress publishing, and plugin demo workflows. Triggers on any /youtube command or YouTube-related marketing request. Always pull live data before generating recommendations.
日本語の概要は準備中です。原文の説明を表示しています。
Build and maintain a provenance-clean proof library — inventory every real proof asset (analytics, reviews, permitted testimonials, case studies, press, certifications), categorize it, rewrite each cleared item in 3 lengths, fuse top assets with narrative, and gate everything through FTC testimonial rules before it can ship. Use when "proof library", "gather our proof", "authority builder", "collect testimonials", "social proof assets", "proof points for the sales page", "what results can we claim", or any request to assemble evidence for marketing claims. NEVER invents proof — missing proof is reported as a gap.
日本語の概要は準備中です。原文の説明を表示しています。
Weekly marketing audit and operating review. Pulls the last 7 days of source-backed marketing, analytics, content, paid media, lead, watcher, and audit data; compares it to the prior 7 days; flags urgent issues; and produces a weekly scorecard plus action list. Use when "weekly audit", "weekly marketing review", "weekly check-in", "weekly scorecard", "what changed this week", "Friday marketing review", or any request for a recurring 7-day marketing audit.
日本語の概要は準備中です。原文の説明を表示しています。