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System Design Building Blocks

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HoangNguyen0403
system-design-building-blocks

Select infrastructure components by the constraint each removes: load balancers, caches and invalidation, queues and pub/sub, CDN, API gateway, rate limiting, consistent hashing. Use when choosing cache, queue, replica, or edge layers; defer engine tuning to the database category.

Overview

PublisherHoangNguyen0403
Repositoryagent-skills-standard
Skill namesystem-design-building-blocks
Stars
573
Forks
166
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by HoangNguyen0403 on GitHub. Read the source before you install it.

Installation

Install the System Design Building Blocks AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/HoangNguyen0403/agent-skills-standard/tree/develop/.agents/skills/system-design/system-design-building-blocks
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/HoangNguyen0403/agent-skills-standard.git /tmp/agent-skills-standard
mkdir -p .claude/skills
cp -r /tmp/agent-skills-standard/.agents/skills/system-design/system-design-building-blocks .claude/skills/system-design-building-blocks
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable System Design Building Blocks in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads System Design Building Blocks on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so System Design Building Blocks is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

System Building Blocks

Priority: P1 (HIGH)

Add a component only to remove a named constraint. Every component adds failure modes and cost.

Selection Table

Constraint observedComponentCost accepted
One instance saturates CPU or connectionsHorizontal scaling behind a load balancerStatelessness required; session moves to a store
Read QPS exceeds store ceiling; data tolerates stalenessRead-through cacheStale reads up to TTL; invalidation complexity
Write spikes exceed sustainable store throughputQueue plus async workerEventual completion; needs idempotent consumers
Slow non-critical work blocks the request pathBackground job or eventExtra delivery guarantees to reason about
Static or media bytes dominate egressCDNCache purge lag; origin still needed for misses
Cross-cutting authn, quota, routing repeated per serviceAPI gatewayCentral chokepoint; must be HA
One tenant or key can exhaust capacityRate limiter or admission controlRejections need clear client contracts
Cache or shard nodes change count during scalingConsistent hashingRebalancing logic; hot-key skew persists

Caching Rules

  • Default to cache-aside for read-heavy paths; use write-through only when read-after-write must be exact.
  • Set TTL from tolerable staleness, not from convenience. Every cached key needs a stated TTL and an invalidation trigger.
  • Guard the miss path: single-flight or request coalescing prevents a stampede when a hot key expires.
  • Never cache what you cannot invalidate. Never cache per-user data under a shared key.

Queue Rules

  • Choose delivery semantics explicitly: at-least-once plus idempotent consumers is the safe default.
  • Partition by the entity that must stay ordered; ordering is per partition, never global.
  • Size the queue for the burst, and define the drain rate. An unbounded queue converts a throughput problem into a latency and memory problem.
  • Apply backpressure at the producer when depth exceeds the drain budget; shedding beats silent growth.

Session State

  • Default to a stateless token (signed JWT or opaque id verified at the edge); the app tier keeps nothing per user.
  • Move to a shared session store (Redis) when sessions must be revocable immediately or carry more than a token can hold.
  • Sticky sessions are a last resort: they survive one deploy badly and block scale-in. Never store session state in app memory.

Edge and Traffic Rules

  • L4 balances connections, L7 routes on content; use L7 when routing needs paths, headers, or canaries.
  • Health checks must test a dependency-aware readiness endpoint, not a static 200.
  • Rate limit at the edge by identity and by cost class; return a retry hint the client can honor.

Anti-Patterns

  • No component without a constraint: a box that solves no stated problem gets removed.
  • No cache as a correctness fix: caching hides a slow query; fix the query, then cache.
  • No queue without a consumer budget: define drain rate and DLQ before shipping.
  • No shared mutable session in app memory: it blocks horizontal scaling.

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the System Design Building Blocks AI skill do?

Select infrastructure components by the constraint each removes: load balancers, caches and invalidation, queues and pub/sub, CDN, API gateway, rate limiting, consistent hashing. Use when choosing cache, queue, replica, or edge layers; defer engine tuning to the database category.

Why use System Design Building Blocks on TypingMind?

Because you install it once and use it with any model. System Design Building Blocks is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install System Design Building Blocks in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/HoangNguyen0403/agent-skills-standard/tree/develop/.agents/skills/system-design/system-design-building-blocks. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use System Design Building Blocks?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with System Design Building Blocks?

As many as you like. As long as a model supports skills, you can use System Design Building Blocks with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the System Design Building Blocks AI skill free?

Yes. It is published on GitHub by HoangNguyen0403 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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