Agent skill

systems-computing

Understand computer systems from digital logic through operating systems, networks, databases, and distributed systems.

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Install this agent skill to your Project

npx add-skill https://github.com/pluginagentmarketplace/custom-plugin-computer-science/tree/main/skills/systems

SKILL.md

Systems Computing Skill

Skill Metadata

yaml
skill_config:
  version: "1.0.0"
  category: systems
  prerequisites: [cs-foundations]
  estimated_time: "10-12 weeks"
  difficulty: intermediate-advanced

  parameter_validation:
    domain:
      type: string
      enum: [cpu, memory, os, network, database, distributed]
      required: true
    scale:
      type: string
      enum: [single, cluster, global]
      default: single

  retry_config:
    max_attempts: 3
    backoff_strategy: exponential
    initial_delay_ms: 500

  observability:
    log_level: INFO
    metrics: [domain_usage, design_pattern_frequency]

Quick Start

Master how modern computers actually work, from circuits to distributed systems.

Digital Logic & CPU

CPU Concepts

  • Instruction execution cycle
  • Registers and cache hierarchy
  • Pipelining
  • Branch prediction

Cache Memory

  • L1, L2, L3 hierarchy
  • Temporal and spatial locality
  • Cache lines and blocks

Operating Systems

Process Management

  • Process states and context switching
  • Scheduling algorithms: FCFS, SJF, round-robin

Memory Management

  • Virtual memory and paging
  • Page tables and TLB
  • Page replacement: LRU, optimal

Concurrency

  • Race conditions and critical sections
  • Mutual exclusion: locks, semaphores
  • Deadlock: conditions, detection, recovery

Networking

OSI Model

  • Layer 1: Physical (signals, cables)
  • Layer 2: Data Link (MAC, switching)
  • Layer 3: Network (IP, routing)
  • Layer 4: Transport (TCP, UDP)

Protocols

  • HTTP/HTTPS: Web
  • TCP: Reliable connection
  • UDP: Fast connectionless
  • DNS: Name resolution

Distributed Systems

CAP Theorem

  • Consistency: all nodes same data
  • Availability: responds to requests
  • Partition tolerance: survives splits
  • Can guarantee only 2 of 3

Consensus Algorithms

  • Paxos: proven consensus
  • Raft: simpler consensus

Troubleshooting

Issue Root Cause Resolution
High latency Slow DB queries Add indexes, cache
Memory exhaustion Memory leak Profile, fix leaks
Connection exhaustion Pool too small Increase pool size
Cascading failure No circuit breaker Add circuit breakers

Key Concepts

  • Latency: Time to complete one task
  • Throughput: Tasks completed per unit time
  • Scalability: Performance with increasing load
  • Fault tolerance: Reliability despite failures

Interview Questions

  • How do caches work?
  • Explain virtual memory
  • What is thrashing?
  • Difference between TCP and UDP?
  • How do transactions work?
  • Design a system that scales to millions of users

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