linkerd-patterns
Implement Linkerd service mesh patterns for security, traffic policy management, and zero-trust networking in Kubernetes environments.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
380 skills found
Implement Linkerd service mesh patterns for security, traffic policy management, and zero-trust networking in Kubernetes environments.
Systematic debugging skill to trace errors backward through call stacks, identify original triggers, and implement layered defenses instead of patching symptoms.
Manage AWS Lambda serverless functions: deploy code, configure event triggers, debug invocations, optimize cold starts, and maintain layers.
Automate GitHub issue triage by analyzing reports against the codebase, verifying technical claims, and providing expert-driven responses to resolve invalid issues.
Expert guidance and configuration standards for creating specialized OpenCode AI agents, including YAML frontmatter, tool permissions, and operational modes.
Development guide for lemline-core, the stateless Serverless Workflow engine. Manage workflow execution, node navigation, state transitions, JQ expression evaluation, error handling, and parallel fork logic.
Design professional-grade brand identities using geometric primitives, negative space, and flat vector-style aesthetics via AI-driven branding logic.
Comprehensive Linux development environment management for compilers, build tools, IDEs, and debugging workflows.
Convert natural language queries to safe, optimized SQL. Automates database interactions with schema awareness and parameterized query generation.
Generate optimized SQL queries from natural language. Supports BigQuery, PostgreSQL, MySQL, and Snowflake. Analyze database schemas, interpret business requirements, and output ready-to-run queries with explanations.
Automates Moonwell protocol governance proposal lifecycle, from creation and verification to deployment and testing.
Token-efficient codebase analysis skill for call graphs, semantic search, impact analysis, and data flow. Saves ~95% tokens vs. raw reads.