AGENT SKILLS · MISSION KIT
Useful agent skills ranked by real adoption
Browse verified skills from public repositories. Compare what each skill does, package contents, install activity, and source evidence before adding it to your agent.
- CATALOG SCOPE
- VERIFIED
- skills
- 23,248
- repositories
- 3589
- last synced
- Nov 4, 2026
every-appcompetitor-analysis
Analyze one competitor's organic footprint, ranking keywords, content themes, backlinks, and gaps.
- 1h installs
- 3
- GitHub stars
- 26.2K
- Updated
- Oct 31
every-appkeyword-clustering
Cluster keywords by intent and map them to existing or proposed pages.
- 1h installs
- 3
- GitHub stars
- 26.2K
- Updated
- Oct 31
every-appkeyword-research
Discover keyword opportunities, evaluate metrics and SERPs, and save/tag promising terms.
- 1h installs
- 3
- GitHub stars
- 26.2K
- Updated
- Oct 31
every-applink-prospecting
Find link prospects, discover contact paths, and draft outreach from SERPs and backlink signals.
- 1h installs
- 3
- GitHub stars
- 26.2K
- Updated
- Oct 31
every-applocal-seo
Audit a Google Business Profile, compare it to local competitors, and map Maps visibility around a location.
- 1h installs
- 3
- GitHub stars
- 26.2K
- Updated
- Oct 31
every-appseo-report
Write and save an OpenSEO report as one self-contained HTML page. Use when a skill has finished its research, and whenever the user asks for a report, check-in, or summary, or names a report template.
- 1h installs
- 3
- GitHub stars
- 26.2K
- Updated
- Oct 31
googleagent-platform-alert-configuration
Configures best-practice alerting policies for AI agents using OpenTelemetry (OTel) metrics, generating output as Terraform (.tf) configuration files. Use when analyzing, writing, or deploying alerting policies to monitor agent latency, error rates, token usage, and quality metrics. Don't use for standard infrastructure monitoring unrelated to AI agents, or when the agent is not instrumented with OpenTelemetry (for Reliability, Cost, Safety, Security alerts). NOTE: Reliability, Cost, Safety, and
- 1h installs
- 3
- GitHub stars
- 21.8K
- Updated
- Nov 3
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 endpo
- 1h installs
- 3
- GitHub stars
- 21.8K
- Updated
- Nov 3
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.
- 1h installs
- 3
- GitHub stars
- 21.8K
- Updated
- Nov 3
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 generating synthetic user scenarios, 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-tun
- 1h installs
- 3
- GitHub stars
- 21.8K
- Updated
- Nov 3
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.
- 1h installs
- 3
- GitHub stars
- 21.8K
- Updated
- Nov 3
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.
- 1h installs
- 3
- GitHub stars
- 21.8K
- Updated
- Nov 3
googleagent-platform-troubleshooting
Troubleshoots Google Cloud Gemini Enterprise Agent Platform issues across Agent Gateway, Agent Connectivity Templates (ACT), Agent Registry, Agent Identity, Identity-Aware Proxy (IAP), Unified Access Policies (UAP), Model Armor, Semantic Governance Policies (SGP), Cloud DNS peering, Private CA TrustConfig, Next-Hop Secure Web Proxy (SWP), Explicit HTTPS Proxy (L4 AuthzPolicy), and Cloud Trace. Use when agent requests fail with 401/403/404/498/500/503 or Code 13, Egress request is not authorized,
- 1h installs
- 3
- GitHub stars
- 21.8K
- Updated
- Nov 3
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).
- 1h installs
- 3
- GitHub stars
- 21.8K
- Updated
- Nov 3
googleapi-gateway-backend-security-and-rate-limiting
Secures and rate limits backend services behind Google Cloud API Gateway across OpenAPI 2.0 and OpenAPI 3.0.x API configurations, including MCP-enabled gateways. Use when configuring API key or JWT authentication, locking down Cloud Run or Cloud Run functions backends with a gateway service account, reading authenticated claims from X-Apigateway-Api-Userinfo, setting per-project request quotas, or diagnosing HTTP 429 and HTTP 500 Service Control Quota errors. Do not use for Apigee, GKE Gateway A
- 1h installs
- 3
- GitHub stars
- 21.8K
- Updated
- Nov 3
googleapi-gateway-mcp-server
Configures Google Cloud API Gateway to act as a remote Model Context Protocol (MCP) server (Public Preview) that exposes REST APIs as agent tools over HTTP (POST /mcp). Use when migrating OpenAPI 2.0 specs to OpenAPI 3.x for MCP, annotating specs with x-google-api-management.mcp and x-google-mcp-tool, securing tools/list with JWTs or API keys, connecting Google ADK (McpToolset) or Apigee API hub and Agent Registry, or troubleshooting MCP JSON-RPC errors (-32601, -32602, -32000). Do not use for A
- 1h installs
- 3
- GitHub stars
- 21.8K
- Updated
- Nov 3
googleapigee-agent-gateway-governance
Stands up an Apigee API proxy that a Google Cloud Agent Gateway calls as an ext-proc (Service Extension) callout on an agent's LLM traffic, to meter token usage per model, extract caller identity, and apply Model Armor prompt screening or a semantic cache. Use when wiring Apigee in as an AI gateway behind an Agent Gateway, when an agent's model egress needs governing, or when a callout proxy returns no verdict and you need to find out why. The distinguishing question is whether Apigee forwards t
- 1h installs
- 3
- GitHub stars
- 21.8K
- Updated
- Nov 3
googleapplication-design-center-design-deploy
Processes GCP infrastructure design and deployment workflows within Application Design Center (ADC). Use when: - Designing GCP infrastructure with Terraform. - Validating local HCL. - Performing best-practice plan scans. - Importing templates to Application Design Center (ADC). - Deploying templates. - Troubleshooting deployment failures. Boundaries: - Only use for GCP-specific cloud infrastructure. - Only use for Terraform coding within the ADC context.
- 1h installs
- 3
- GitHub stars
- 21.8K
- Updated
- Nov 3
googleapplication-integration-authoring
Builds, versions, publishes, tests, and executes Google Cloud Application Integration workflows through the REST API and Python discovery client, and promotes versions across environments. Use when listing integrations, downloading or uploading integration versions as JSON, configuring API triggers or config variables, publishing drafts, invoking integrations, or automating CI/CD promotion. Do not use for initial region provisioning and IAM setup (use application-integration-basics) or diagnosin
- 1h installs
- 3
- GitHub stars
- 21.8K
- Updated
- Nov 3
googleapplication-integration-troubleshooting
Diagnoses failed, stuck, or silent Google Cloud Application Integration runs and Integration Connectors tasks using the REST API, Cloud Logging, and Cloud Monitoring. Use when an integration fails, returns HTTP 200 without doing the expected work, hangs in a suspended or retry state, or hits IAM, run-as service account, connector health, or quota errors. Do not use for initial region provisioning (use application-integration-basics) or building and deploying versions (use application-integration
- 1h installs
- 3
- GitHub stars
- 21.8K
- Updated
- Nov 3
googleassured-workloads-basics
Provisions, inspects, updates, and deletes Google Cloud Assured Workloads V1 compliant folders, CMEK settings, Sovereign Controls by Partners, and service usage restrictions. Use when creating, listing, describing, updating, or deleting an Assured Workloads workload for any compliance regime or data boundary (FedRAMP, DoD IL2/IL4/IL5, ITAR, CJIS, Healthcare, Sovereign Controls by Partners, or Regional Data Boundaries). Don't use for brownfield assessments or custom frameworks (use assuredworkloa
- 1h installs
- 3
- GitHub stars
- 21.8K
- Updated
- Nov 3
googleassuredworkloads-environment-assessor
Discover Google Cloud resource telemetry and effective Org Policies, evaluate brownfield workloads against sovereign data boundary and compliance standards (EU Data Boundary with Support, FedRAMP Moderate/High, DoD IL4/IL5, ITAR, CJIS, US/EU Regional Data Boundaries), and recommend the optimal Assured Workloads Framework. Use when asked to: "assess my environment for compliance", "which Assured Workloads framework should I use?", "check if my folder is ready for EU sovereignty", "evaluate compli
- 1h installs
- 3
- GitHub stars
- 21.8K
- Updated
- Nov 3
googlebigquery-observability
Provides data-retrieval best practices, tool selection guidance, and performant SQL query syntax for BigQuery telemetry across INFORMATIONSCHEMA, Cloud Monitoring, and the REST API. Use when the telemetry to fetch is already known, selecting telemetry tools, writing performant INFORMATIONSCHEMA queries, retrieving telemetry for diagnosing single-job performance bottlenecks, investigating slot contention, job concurrency and queue latency, analyzing reservation capacity, utilization and autoscali
- 1h installs
- 3
- GitHub stars
- 21.8K
- Updated
- Nov 3
googlebigquery-troubleshooting
Provides diagnostic workflows and step-by-step root-cause analysis procedures for actively broken, failing, or slow BigQuery jobs, execution graph and query plan stage bottlenecks, system performance issues, or unexpectedly expensive workloads. Use when interpreting symptoms, isolating bottlenecks, diagnosing cost spikes (on-demand query spend, capacity slot autoscaling, storage growth), execution graph stages or substep variables, identifying root causes, and determining remediation steps. Don'
- 1h installs
- 3
- GitHub stars
- 21.8K
- Updated
- Nov 3