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When the user wants to create or update their app marketing context document. Also use when the user mentions "app context", "marketing brief", "app positioning", or when starting any ASO or app marketing project. This is the foundation skill — all other skills check for this context first.
When the user wants to plan a launch strategy for a new app or major update. Also use when the user mentions "app launch", "launch plan", "launch checklist", "pre-launch", "launch day", or "how to launch my app". For ongoing ASO after launch, see aso-audit. For paid acquisition during launch, see ua-campaign.
Email marketing skill for Claude Code.
When the user wants to design, test, or improve their app icon to increase tap-through rate and conversions in App Store search and browse. Use when the user mentions "app icon", "icon design", "icon A/B test", "icon variants", "tap-through rate", "icon conversion", "icon refresh", or wants to know what makes a good app icon. For screenshot optimization, see screenshot-optimization. For full listing A/B tests, see ab-test-store-listing.
When the user wants to implement, optimize, or use App Clips for app discovery and conversion. Use when the user mentions "App Clip", "app clip code", "mini app", "instant app", "App Clip card", "App Clip link", "no download required", "instant experience", or wants to understand how App Clips appear in App Store search. For general App Store discoverability, see aso-audit. For marketing campaigns, see ua-campaign.
Agent skills for Qdrant vector search: scaling, performance optimization, search quality, monitoring, deployment, edge, model migration, version upgrades, and SDK usage
When the user wants to set up, interpret, or improve their app analytics and tracking. Also use when the user mentions "analytics", "tracking", "metrics", "KPIs", "App Store Connect analytics", "install tracking", "funnel", "attribution", or "how is my app performing". For A/B testing, see ab-test-store-listing. For retention metrics, see retention-optimization.
When the user wants to optimize their Google Play Store listing — title, short description, full description, keywords, ratings, or Play Store-specific features. Use when the user mentions "Google Play", "Android", "Play Store", "Play Console", "short description", "full description indexed", "Google Play ASO", or wants Google Play-specific keyword, creative, or ratings strategy. For iOS App Store optimization, see aso-audit and metadata-optimization.
Create, update, and fix Cypress tests. Connect to Cypress Cloud to see test results and use data to manage your test suite.
When the user wants to A/B test App Store product page elements to improve conversion rate. Also use when the user mentions "A/B test", "product page optimization", "test my screenshots", "test my icon", "conversion rate optimization", "CPP", or "custom product pages". For screenshot design, see screenshot-optimization. For metadata optimization, see metadata-optimization.
Agent Platform Model Tuning. Use when you need to fine-tune open models or Gemini models using Agent Platform infrastructure. Don't use for model training outside Agent Platform, model deployment to endpoints (use agent-platform-deploy), or managing serving endpoints (use agent-platform-endpoint-management).
Manages GenAI tuning jobs in Agent Platform. Use this to list, get, or cancel ongoing model tuning jobs. Don't use for fine-tuning models (use agent-platform-tuning), deploying models to endpoints (use agent-platform-deploy), or managing serving endpoints (use agent-platform-endpoint-management).
Redis development best practices — data structures, query engine, vector search, caching, and performance optimization
Interact with the Gemini Enterprise Agent Platform Skill Registry to create and search for available skills. Use this skill to enable agents to register functionality or discover new capabilities.
Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google Workspace RAG, or other RAG products like gRAG.
Redis Search guidance covering FT.CREATE schema design, field type selection (TEXT, TAG, NUMERIC, GEO, GEOSHAPE, VECTOR, JSON path), DIALECT 2 query syntax, FT.SEARCH / FT.AGGREGATE / FT.HYBRID command selection, vector similarity with HNSW or FLAT, hybrid retrieval combining lexical and vector ranking, RAG pipelines, zero-downtime index updates via aliases, and debugging with FT.PROFILE and FT.EXPLAIN. Use when defining a search index on Hash or JSON documents, writing FT.SEARCH queries with filters, sorting, aggregation, or vector KNN, tuning HNSW parameters, building a RAG retrieval pipeline, or troubleshooting slow or empty search results.
Agent Skills for Google products and technologies
Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.
Redis observability guidance — which metrics to monitor (memory, connections, hit ratio, ops/sec, rejected connections), which built-in commands to reach for during incident triage (SLOWLOG, INFO, MEMORY DOCTOR, CLIENT LIST, FT.PROFILE), and when to use the Redis Insight GUI. Use when setting up monitoring or alerts for a Redis instance, diagnosing a performance regression, profiling a slow FT.SEARCH query, or wiring Redis metrics into Prometheus, Datadog, or similar.
Guides agents and users through migrating from Gemini API in Google AI Studio to Gemini Enterprise Agent Platform (formerly Vertex AI). Use this skill when moving applications to Google Cloud, to leverage Cloud credits, or to unify inferencing with other Cloud infrastructure (IAM, billing, telemetry).
Connects to and performs inference with Google Cloud Agent Platform GenAI models, including First-Party Gemini models and Third-Party OpenMaaS models (Llama, DeepSeek, Qwen, etc.). Use when you need to generate code for calling Gemini or OpenMaaS models, authenticate with GenAI SDK, OpenAI SDK, or legacy Agent Platform SDK, configure base URLs and global/regional endpoints, or troubleshoot 429 Resource Exhausted (DSQ), 400 User Validation, or 404 Not Found errors. Don't use for deploying models to endpoints or for running model evaluations.
Core Redis modeling guidance — choose the right data structure (String, Hash, List, Set, Sorted Set, JSON, Stream, Vector Set) and use consistent colon-separated key names. Use when designing a Redis data model, caching objects, deciding between Hash and JSON, building counters, leaderboards, membership sets, or session stores, or when reviewing/cleaning up Redis key naming.
Measures and improves the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology. Use when evaluating an agent or model, building an eval dataset, picking or writing evaluation metrics, analyzing failures, comparing results before and after a fix, or when guidance is needed on Agent Platform eval methodology — including dataset schema, LLM-as-judge scoring, and common failure causes. For fine-tuning, use agent-platform-tuning. For general production deployment, use agent-platform-deploy.
Manages Agent Platform serving endpoints. Use when you need to create, list, describe, update, or delete serving endpoints for model deployment on Agent Platform. Also use when troubleshooting endpoint permission, quota, or resource busy errors. Don't use for deploying models to endpoints or for running model evaluations.
Redis client and connection guidance covering connection pooling, multiplexing, pipelining, client-side caching with RESP3, avoiding slow commands (KEYS, SMEMBERS, HGETALL), and tuning socket timeouts. Use when configuring a Redis client (redis-py, Jedis, Lettuce, NRedisStack), batching commands for throughput, eliminating per-request connection creation, iterating large keyspaces with SCAN, enabling client-side caching for read-heavy workloads, or setting connect and read timeouts.
Deploy open models or custom weights from Model Garden to Agent Platform endpoints, check the status of an in-progress deployment operation, or clean up resources by undeploying models and deleting endpoints. Use when asked to actively deploy a model, list the Model Garden CATALOG of available models, check if a specific model is deployable (gcloud ai model-garden models list-deployment-config), query deployment cost, troubleshoot deployment errors (like quota limits), or undeploy/clean up endpoints. Also use when copying and deploying a 1P Tuned Model. Don't use for pure listing/discovery questions of the form "is X deployed?", "list my endpoints", or "which regions have models running?" — for those use agent-platform-endpoint-management. Don't use for public Vertex AI deployments (use the vertex-deploy skill) or for running model evaluations (use the agent-platform-eval-flywheel skill).
Configures best-practice alerting policies for AI agents using OpenTelemetry (OTel) metrics. Use when analyzing, writing, or deploying alerting policies to monitor agent latency, error rates, token usage, and quality metrics. NOTE: Reliability, Cost, Safety, and Security alerts use generic OTel metrics and work across runtimes (e.g., Cloud Run, Vertex AI). Quality alerts rely on Vertex AI Online Monitors and are strictly bound to Vertex AI deployments.
Redis Cluster and replication guidance covering hash tags for multi-key operations, avoiding CROSSSLOT errors, and reading from replicas to scale read-heavy workloads. Use when designing keys for a sharded Redis Cluster, debugging CROSSSLOT errors on MGET / SDIFF / pipelines, configuring a multi-key transaction in a cluster, or routing reads to replicas for caches, analytics, or dashboards.
Manages Google Analytics reporting data, enables the Analytics Data API via the Cloud CLI, and creates reports using the Google Analytics Data API (v1beta). Use when you need to interact with Google Analytics properties, run customized analytics reports, query metrics (like activeUsers, screenPageViews) and dimensions (like city, date), check metrics and dimensions compatibility, or verify API enablement. Don't use for Google Analytics Admin API operations (e.g., creating properties, managing users) or for front-end tracking installation.
Manages Google Analytics account and property settings, enables the Analytics Admin API via the Cloud CLI, lists accounts and properties, and manages data streams, custom dimensions, conversion events, and integrations. Use when you need to programmatically configure Google Analytics accounts, provision properties, manage data retention, configure Measurement Protocol secrets, or manage Firebase and Google Ads links.
Iris is Redis's umbrella for AI-focused products. Use this skill when integrating with the Iris Redis Agent Memory (RAM) data plane on Redis Cloud — recording session events for an AI agent, creating or searching long-term memories, configuring a memory store, or tuning background memory promotion. Code examples use the official redis-agent-memory (Python) and @redis-iris/agent-memory (TypeScript) SDKs.
Use this skill for Interactive Media Ads (IMA) SDK client-side ad insertion when you are requesting video ads client-side into websites, apps, TVs or other platforms with VAST or VMAP. Do not use for Dynamic Ad Insertion (DAI), SSAI, or SGAI (use the ima-sdk-dai-basics skill instead).
Provides instructions for implementing, integrating, or configuring
Official agent skills for the Venice.ai API — private-by-default inference for chat, images, video, audio, embeddings, characters, billing, wallet (x402), and crypto RPC.
Provides instructions for implementing, integrating, or configuring
Provides instructions for integrating the Google Mobile Ads (GMA)
Use when building notifications with Courier across email, SMS, push, in-app inbox, Slack, Teams, or WhatsApp. Covers transactional messages (password reset, OTP, orders, billing), growth notifications (onboarding, engagement, referral), multi-channel routing, preferences and topics, reliability and webhooks, journeys (multi-step notification sequences via API), template CRUD and Elemental content, routing strategies, provider configuration, the Courier CLI and MCP server, and migrations from Knock, Novu, or other notification systems.
Provides instructions to implement, integrate, or configure Google Mobile Ads (GMA) banner ads in Android, iOS, or Unity mobile applications. Use when the task involves setting up banner ads in a mobile application. Don't use for other ad formats like interstitial or rewarded ads.
Migrates Android applications from the old, legacy Google Mobile
Rephrase tasks and requests by avoiding Demand Avoidance triggers for someone with PDA autism spectrum disorder. It transforms demands into exploration and autonomous actions.
Guides developers through Google Ads API quickstart: credential setup, choosing from 6 client libraries/REST, configuring environments, and running a "retrieve campaigns" script. Troubleshoots common setup errors: USERPERMISSIONDENIED, logincustomerid issues, and DEVELOPERTOKENNOTAPPROVED. Use this skill when: - The user asks how to get started with the Google Ads API. - The user needs to set up Google Ads credentials or developer tokens. - The user wants to write a quickstart/example script for Google Ads. - The user encounters errors like USERPERMISSIONDENIED or DEVELOPERTOKENNOTAPPROVED.
Guides developers through downloading, configuring, and installing the official open-source Google Ads MCP Server. Use this skill when a user wants to connect their AI assistant (such as Gemini, Claude Code, or Cursor) to their Google Ads account to query campaigns or retrieve reporting metrics using natural language.
Run a 5-minute personal standup for a solo dev — what shipped yesterday, what's blocked, what's next today. Use when the user asks for a daily check-in, says "what should I work on today", "what did I do yesterday", or wants to break out of a productivity slump.
Guides developers through client library installation and authentication setup steps for the Data Manager API. Use this skill when a user is getting started with the Data Manager API and needs to setup their local environment, install the client library, or setup access to the API. Don't use for implementing audience or event ingestion logic (use the data-manager-api-audience-ingestion or data-manager-api-event-ingestion skills instead).
Agent Skills for Google products and technologies
Force a fast, regret-minimizing product decision when a solo founder is stuck choosing between options. Use when the user is paralyzed by a binary or tri-way choice (build A vs B, ship now vs polish, free vs paid, etc.), says "I can't decide", "should I", or asks for a sanity check on a roadmap call.
Guides developers through managing (adding, removing, and clearing) audience members for Google products using the Data Manager API and its associated client libraries. Use this skill when the user wants to upload audience members, remove specific users, or clear/replace an entire audience for Customer Match, mobile device ID audiences, or any other audience use case supported by the Data Manager API. Don't use for uploading events or conversions (use the data-manager-api-event-ingestion skill).
Run a lightweight, blame-free postmortem after an incident, failed launch, or missed deadline — for one person. Use when the user says "that didn't go well", "the launch flopped", "we had an outage", "I missed my deadline", or wants to learn from a recent failure.