cloud-design-patterns
Covers 42 distributed system design patterns spanning reliability, performance, messaging, security, and deployment. Supports designing, reviewing, and implementing cloud architectures.
Your agent can do more. Find the skill that makes it happen.
Find your next superpower If you are an agent, refer to our llms.txt for full access.Covers 42 distributed system design patterns spanning reliability, performance, messaging, security, and deployment. Supports designing, reviewing, and implementing cloud architectures.
Explores wiki knowledge according to which AI tool produced it. Compares memories across tools and surfaces unique knowledge, differences, and blind spots from any project.
Run the daily wiki maintenance cycle: check all source freshness, update the index, and regenerate hot.md. Use this skill when the user says "/daily-update", "run the daily update", "update everything", "morning sync", "refresh the wiki index", or when triggered by the scheduled 9 AM run (launchd, systemd timer, or cron). Also use to set up or verify the cron + terminal notification infrastructure…
Analyzes Rust question intent across implementation, design, best practices, and library comparisons. Covers compiler errors, ownership, borrowing, lifetimes, traits, concurrency, and error handling.
Analyzes reasoning in written content when an explicit argument critique is requested. Its scope excludes code analysis.
Sets up the OpenTelemetry Collector with Sentry Exporter. Supports multi-project telemetry routing, automatic project creation, and trace and log pipelines across multiple services.
Supports end-to-end and integration tests using Jest, supertest, real Docker infrastructure, and Given-When-Then patterns. Covers test setup, execution, review, isolation, flaky tests, and Kafka or Redpanda consumers.
Supports adding a new sound effect to @remotion/sfx.
Guides Mojo code that calls Python libraries or exposes Mojo types and functions to Python. Covers Python extension modules, wrapping Mojo structs, and converting between Python and Mojo types.
Guides discovery of real needs and constraints. Helps identify problems in requirements.
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
Initiate voice calls using OpenClaw's voice-call plugin.
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