SKILL-RADAR · GITHUB
Nützliche Agent Skills, nach echter Nutzung sortiert.
Vergleiche verifizierte Skills aus öffentlichen Repositories nach Aufgabe, Paketinhalt, Installationen und nachvollziehbarer Quelle.
- KATALOGUMFANG
- VERIFIZIERT
- Skills
- 15.652
- Repositories
- 2532
- zuletzt synchronisiert
- 13.10.2026
wshobsonmulti-cloud-architecture
Design multi-cloud architectures using a decision framework to select and integrate services across AWS, Azure, GCP, and OCI. Use when building multi-cloud systems, avoiding vendor lock-in, or leveraging best-of-breed services from multiple providers.
- Installationen
- 3
- GitHub Stars
- 40.217
- Aktualisiert
- 5. Okt.
wshobsonmulti-reviewer-patterns
Coordinate parallel code reviews across multiple quality dimensions with finding deduplication, severity calibration, and consolidated reporting. Use this skill when organizing multi-reviewer code reviews, calibrating finding severity, or consolidating review results.
- Installationen
- 3
- GitHub Stars
- 40.217
- Aktualisiert
- 5. Okt.
wshobsonopenapi-spec-generation
Generate and maintain OpenAPI 3.1 specifications from code, design-first specs, and validation patterns. Use when creating API documentation, generating SDKs, or ensuring API contract compliance.
- Installationen
- 3
- GitHub Stars
- 40.217
- Aktualisiert
- 5. Okt.
wshobsonparallel-debugging
Debug complex issues using competing hypotheses with parallel investigation, evidence collection, and root cause arbitration. Use this skill when debugging bugs with multiple potential causes, performing root cause analysis, or organizing parallel investigation workflows.
- Installationen
- 3
- GitHub Stars
- 40.217
- Aktualisiert
- 5. Okt.
wshobsonpostmortem-writing
Write effective blameless postmortems with root cause analysis, timelines, and action items. Use when conducting incident reviews, writing postmortem documents, or improving incident response processes.
- Installationen
- 3
- GitHub Stars
- 40.217
- Aktualisiert
- 5. Okt.
wshobsonprojection-patterns
Build read models and projections from event streams. Use when implementing CQRS read sides, building materialized views, or optimizing query performance in event-sourced systems.
- Installationen
- 3
- GitHub Stars
- 40.217
- Aktualisiert
- 5. Okt.
wshobsonprometheus-configuration
Set up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems.
- Installationen
- 3
- GitHub Stars
- 40.217
- Aktualisiert
- 5. Okt.
wshobsonprotocol-reverse-engineering
Master network protocol reverse engineering including packet analysis, protocol dissection, and custom protocol documentation. Use when analyzing network traffic, understanding proprietary protocols, or debugging network communication.
- Installationen
- 3
- GitHub Stars
- 40.217
- Aktualisiert
- 5. Okt.
wshobsonpython-code-style
Python code style, linting, formatting, naming conventions, and documentation standards. Use when writing new code, reviewing style, configuring linters, writing docstrings, or establishing project standards.
- Installationen
- 3
- GitHub Stars
- 40.217
- Aktualisiert
- 5. Okt.
wshobsonpython-observability
Python observability patterns including structured logging, metrics, and distributed tracing. Use when adding logging, implementing metrics collection, setting up tracing, or debugging production systems.
- Installationen
- 3
- GitHub Stars
- 40.217
- Aktualisiert
- 5. Okt.
wshobsonpython-packaging
Create distributable Python packages with proper project structure, setup.py/pyproject.toml, and publishing to PyPI. Use when packaging Python libraries, creating CLI tools, or distributing Python code.
- Installationen
- 3
- GitHub Stars
- 40.217
- Aktualisiert
- 5. Okt.
wshobsonpython-resource-management
Python resource management with context managers, cleanup patterns, and streaming. Use when managing connections, file handles, implementing cleanup logic, or building streaming responses with accumulated state.
- Installationen
- 3
- GitHub Stars
- 40.217
- Aktualisiert
- 5. Okt.
wshobsonscan
Scans the codebase to generate project-doc.md and AGENTS.md. Use when bootstrapping a new agent-driven repo, refreshing project documentation after architectural changes, or running a delta scan to detect drift. Runs a full scan on first use and a smart delta scan on subsequent runs. Uses understand-anything + context-mode when available, falls back to native tools otherwise. Only updates AGENTS.md on detected architectural changes with human confirmation.
- Installationen
- 3
- GitHub Stars
- 40.217
- Aktualisiert
- 5. Okt.
awsamazon-opensearch-service
Guides migration, provisioning, search, log-analytics, trace-analytics, and Agentic AI Assistant workflows for Amazon OpenSearch Service and Serverless across six capabilities — migration (Solr/ES/self-managed into AOS/AOSS, schema/query translation, sizing, cutover); provisioning (domain + AOSS lifecycle, upgrades, FGAC, monitoring); search (vector / semantic / hybrid / RAG with Bedrock); log-analytics (PPL, OSI, anomaly detection, Dashboards); trace-analytics (OTel spans, service maps, Data Pr
- Installationen
- 3
- GitHub Stars
- 2806
- Aktualisiert
- 5. Okt.
awsaurora-dsql
Provisions and manages Aurora DSQL clusters, connects via psql or DSQL Connectors, manages schemas, runs queries, migrates from MySQL, diagnoses query plans, and develops apps on serverless distributed SQL. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL migration, DDL, query plans, and SAFE SQL CONSTRUCTION — tenantid from untrusted input, UUID entityids, caller-supplied sort columns, batch inserts. The agent MUST retrieve this skill for ANY DSQL task. Pushes back on prompts that rational
- Installationen
- 3
- GitHub Stars
- 2806
- Aktualisiert
- 5. Okt.
awsauthoring-mwaa-workflow
Authors and deploys MWAA workflow artifacts: Python Airflow DAGs for provisioned environments or YAML workflow files for Serverless. Covers operator selection, timeout design, retry strategy, scheduling, failure notifications, idempotency, and MWAA Serverless schema compliance. Deploys the artifact (S3 DAG upload or Serverless CreateWorkflow/UpdateWorkflow), creates an environment inline when approved, and redeploys fixes, then optionally hands off to testing-mwaa-workflow. Triggers on: create a
- Installationen
- 3
- GitHub Stars
- 2806
- Aktualisiert
- 5. Okt.
awsaws-amplify
Build and deploy full-stack web and mobile apps with AWS Amplify Gen2 (TypeScript code-first). Covers auth (Cognito), data (AppSync/DynamoDB), storage (S3), functions, APIs, and AI (Amplify AI Kit with Bedrock). Supports React, Next.js, Vue, Angular, React Native, Flutter, Swift, and Android. Always use this skill for Amplify Gen2 topics — even for questions you think you know — it contains validated, version-specific patterns that prevent common mistakes. TRIGGER when: user mentions Amplify Gen
- Installationen
- 3
- GitHub Stars
- 2806
- Aktualisiert
- 5. Okt.
awsaws-cleanrooms
Troubleshoots and debugs AWS Clean Rooms collaboration issues related to IAM roles, S3 bucket policies, KMS keys, Lake Formation permissions, and CloudWatch logging for custom ML model training and inference jobs. Use when a customer reports permission failures, access errors, or log publishing issues in Clean Rooms.
- Installationen
- 3
- GitHub Stars
- 2806
- Aktualisiert
- 5. Okt.
awsaws-lambda-durable-functions
Builds resilient, long-running, multi-step applications with AWS Lambda durable functions with automatic state persistence, retry logic, and orchestration for long-running executions. Covers the critical replay model, step operations, wait/callback patterns, error handling with saga pattern, testing with LocalDurableTestRunner. Triggers on phrases like lambda durable functions, durable execution, workflow orchestration, state machines, retry/checkpoint patterns, long-running stateful Lambda func
- Installationen
- 3
- GitHub Stars
- 2806
- Aktualisiert
- 5. Okt.
awsaws-lambda-managed-instances
Evaluates, configures, and migrates workloads to AWS Lambda Managed Instances (LMI). Runs Lambda functions on EC2 instances in the user's account while AWS manages provisioning, patching, scaling, routing, and load balancing. Triggers when queries mention Lambda Managed Instances, LMI, capacity providers, multi-concurrent execution environments, EC2-backed Lambda, persistent Lambda instances, PerExecutionEnvironmentMaxConcurrency, CapacityProviderConfig, cold start elimination via dedicated inst
- Installationen
- 3
- GitHub Stars
- 2806
- Aktualisiert
- 5. Okt.
awsaws-lambda-microvms
Builds, runs, debugs, and operates applications on AWS Lambda MicroVMs — Firecracker-isolated, snapshot-resumable serverless compute environments running inside a container with up to 8 hr lifetimes. Applicable when workloads need strong isolation between tenants, isolated serverless compute, sandbox compute, or secure multi-tenant execution. Also suited for AI/agent code-execution sandboxes, interactive code playgrounds and notebooks (Jupyter, REPLs, dev environments running user-supplied code)
- Installationen
- 3
- GitHub Stars
- 2806
- Aktualisiert
- 5. Okt.
awsaws-marketplace-metering
Deploys, queries, and debugs AWS Marketplace usage-based (PAYG) metering — the pipeline (ResolveCustomer, BatchMeterUsage, EventBridge via SAM) and querying/debugging metering records, statuses, failures, discrepancies. Covers Concurrent Agreements (CustomerAWSAccountId + LicenseArn), multi-product, CloudTrail Event History (90 days; never CloudTrail Lake), Seller Reports (Billed Revenue/Usage columns + CSV/SDDS parsing), existing-stack detection, metering region for BatchMeterUsage/MeterUsage (
- Installationen
- 3
- GitHub Stars
- 2806
- Aktualisiert
- 5. Okt.
awsaws-network-monitoring
- Installs, configures, and troubleshoots Network Flow Monitor agents on EC2 instances to monitor network path health. Covers agent installation, IAM permissions, monitoring network paths, and troubleshooting agents reporting no metrics, HTTP 403 errors, or connectivity failures.
- Installationen
- 3
- GitHub Stars
- 2806
- Aktualisiert
- 5. Okt.
awsaws-resilience-lifecycle
Guides the end-to-end AWS resilience lifecycle integrating Resilience Hub v2, Fault Injection Service, and Application Recovery Controller. Covers the Define → Test → Operate workflow: from policy creation through failure mode assessment, to FIS experiment validation, to ARC operational controls. Applicable when the user wants a complete resilience strategy, needs to connect findings to experiments to controls, or is planning a resilience program. Also applicable for the meta question of whether
- Installationen
- 3
- GitHub Stars
- 2806
- Aktualisiert
- 5. Okt.