Concurrency Patterns
CheckedImplements robust concurrency patterns like producer-consumer and thread pools for efficient parallel task execution.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
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terminal$ npx skills add aj-geddes/useful-ai-prompts --skill concurrency-patterns -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
aj-geddes
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Install target
Live repository
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Automated safety checks
This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.
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SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
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Scanned aj-geddes/useful-ai-prompts at 3f5182cfd7.
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- Commit
- 3f5182cfd7
- Scanned
- 9 files, 710 lines
About this skill
What it does
This skill provides AI agents with a library of concurrency patterns to manage parallel execution and synchronization in multi-threaded or distributed systems. It enables agents to safely coordinate tasks, handle race conditions, and optimize performance when processing independent operations simultaneously.
When to use it
- Parallel Data Processing: When an agent needs to fetch data from multiple APIs concurrently rather than sequentially to reduce latency.
- Task Orchestration: For coordinating complex workflows where sub-tasks must complete before a final aggregation step occurs.
- Resource Management: When managing limited system resources (like database connections) across multiple simultaneous requests.
- Fault Tolerance: To implement retry logic or circuit breakers that handle failures in one thread without blocking others.
Key capabilities
- Implements standard concurrency primitives like mutexes, semaphores, and condition variables.
- Facilitates asynchronous task scheduling and execution queues.
- Provides mechanisms for deadlock detection and prevention strategies.
- Supports parallel map-reduce operations for large datasets.
Example prompts
- "Generate a Python script using
asyncioto fetch weather data from five different cities concurrently without blocking the main thread." - "Explain how to implement a producer-consumer pattern in Go to handle a queue of incoming API requests efficiently."
- "Create a concurrency-safe counter in Rust that increments atomically across multiple goroutines."
Tips & gotchas
Ensure your AI agent understands the specific programming language's concurrency model (e.g., threads vs. async/await) before applying these patterns, as misuse can lead to deadlocks or data corruption. Always test concurrent logic under load to verify race condition handling and performance gains.