RADAR SKILL · GITHUB
Agent Skills utili, ordinati per utilizzo reale.
Confronta Skills verificati per funzione, contenuto del pacchetto, installazioni e affidabilità della fonte.
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- Skills
- 5771
- repository
- 824
- ultimo aggiornamento
- 8 set 2026
agricidanielseo-technical
Technical SEO audit across 9 categories: crawlability, indexability, security, URL structure, mobile, Core Web Vitals, structured data, JavaScript rendering, and IndexNow protocol. Use when user says "technical SEO", "crawl issues", "robots.txt", "Core Web Vitals", "site speed", or "security headers".
- installazioni
- 3
- GitHub Stars
- 16,5K
- Aggiornato
- 26 ago
googleagent-platform-deploy
- 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).
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googleagent-platform-endpoint-management
- 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.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googleagent-platform-eval-flywheel
- 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.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googleagent-platform-inference
- 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 asked to perform inference, ask a model a question, run a test prompt, execute chat completions, or 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.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googleagent-platform-migrate-from-ai-studio
- 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).
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googleagent-platform-model-registry
- 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.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googleagent-platform-prompt-management
- Manages and orchestrates prompts in Agent Platform. Use when you need to create, list, retrieve, version, or delete managed prompts in Agent Platform. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform prompts.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googleagent-platform-rag-engine-management
- 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.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googleagent-platform-skill-registry
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.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googleagent-platform-troubleshooting
- Troubleshoots Google Cloud Gemini Enterprise Agent Platform issues (Agent Gateway, Registry, Identity, Policies, Model Armor, Identity-Aware Proxy (IAP)). Use when agent requests fail with 403 (especially unauthorized egress), Agent Runtime queries return 500, or gateway/IAP logs show permission errors. Don't use for general Google Cloud Identity and Access Management (IAM) debugging or networking issues unrelated to the Agent Platform stack.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googleagent-platform-tuning
- 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).
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googleagent-platform-tuning-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).
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googlealloydb-basics
- Manages clusters, instances, and backups for AlloyDB for PostgreSQL, and integrates with AlloyDB Model Context Protocol (MCP) tools for automated database operations. Use when creating, configuring, or administering AlloyDB databases. Do NOT use for general PostgreSQL instances (e.g. Cloud SQL) or other GCP databases.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googlebigquery-ai-ml
- Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management requests.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googlebigquery-basics
- Manages datasets, tables, and jobs in BigQuery. Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources (datasets, tables, views), or perform basic data ingestion and analysis.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googlebigquery-bigframes
- Generates Python code using BigQuery DataFrames (BigFrames), the pandas/scikit-learn-style API over BigQuery. Use when writing BigFrames code or doing pandas-style dataframe/ML work against BigQuery (e.g. in a notebook). Don't use for SQL-first workflows or the google-cloud-bigquery client library — use bigquery-basics.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googlebigtable-basics
- Assists in provisioning instances/tables, designing performant schemas, and querying data in Bigtable. Use when designing Bigtable row keys, configuring column families, writing SQL queries or client library code (Java, Go, Python) for Bigtable, or diagnosing performance/hotspotting issues. Also use when provisioning Bigtable clusters using gcloud or cbt CLIs. Don't use for generic Cloud SQL administration.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googlecloud-build-basics
- Teaches the fundamentals of Google Cloud Build (GCB). Covers core concepts, API enablement, console navigation to the Build History page, and the end-to-end workflow for creating and manually running a basic build trigger. Do not use for managing private pools or complex pipeline architectures.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googlecloud-databases-onboarding
- Guides users through discovering their database requirements, recommends a Google Cloud database based on a recommendation matrix, and assists in database creation. Use when a user asks 'What database service should I use?', 'Help me pick a database', or when a user wants to create a new database on Google Cloud. Don't use for general Google Cloud maintenance, managing existing databases, or database migrations.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googlecloud-logging-configuration-basics
- Configure single-project Google Cloud Logging: regional log buckets, log sinks, log views, restricting or hiding sensitive logs in the default view (Default) filter, IAM permissions for views (Logs View Accessor, IAM conditions), logs-based metrics, log exclusions, and sampling. Don't use for cross-project logging or multi-project setups.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googlecloud-logging-cross-project-configuration
- Configure and troubleshoot Google Cloud cross-project centralized logging and read-time aggregation. Use when: - Setting up log routing from multiple projects/folders/organizations to a central log bucket. - Creating cross-project log sinks and configuring central log buckets. - Troubleshooting cross-project routing. Don't use for single-project basic configurations.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googlecloud-logging-query-generation
- Generates Logging Query Language (LQL) queries for Google Cloud Logging from natural language. Use this skill when you need to query log data or when you are debugging issues. You can filter log data by Google Cloud service. Don't use this skill to query other databases, such as SQL or Cloud Spanner.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set
googlecloud-monitoring-chart-generation
- Generates Google Cloud Monitoring Server-Driven UI (SDUI) Widget and XyChart Protocol Buffer textprotos from resolved PromQL or ListTimeSeries queries. Use when: - Generating valid google.monitoring.dashboard.v1.Widget textprotos, containing PrometheusQuery or TimeSeriesFilter datasets, for use with the Cloud Monitoring Dashboards API, gcloud CLI, or declarative dashboard definitions. - Synthesizing Server-Driven UI (SDUI) widget titles, axis labels, and plot types for Prometheus or ListTimeSeries queries. Don't use for: - Metric discovery or PromQL query generation. For those tasks, use the cloud-monitoring-metric-selection or cloud-monitoring-promql-query skills.
- installazioni
- 3
- GitHub Stars
- 19,6K
- Aggiornato
- 6 set