nw-sd-case-studies

nw-sd-case-studies is a skill for Claude Code from nWave-ai/nWave. It costs 40 tokens per session (2,865 once invoked), scanned A, original, MIT.

A reference guide containing 25 real-world system design case studies, such as rate limiters, key-value stores, and messaging systems. Each case explains requirements, architecture, and important design choices.

In plain words
What is it for?
It helps compare architecture options, study common distributed-system designs, and prepare for system design interviews.
Why use it?
It provides prior examples when you need to design a system but are unsure which structures and trade-offs to consider.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Good fit It helps compare architecture options, study common distributed-system designs, and prepare for system design interviews.

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Install with agentmods
npx agentmods add skills/nwave-ai/nwave/nw-sd-case-studies
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add nWave-ai/nWave --skill nw-sd-case-studies
Clone the repo
git clone --depth 1 https://github.com/nWave-ai/nWave

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for nw-sd-case-studies

README.md
[![agentmods](https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-sd-case-studies.svg)](https://agentmods.dev/skills/nwave-ai/nwave/nw-sd-case-studies)
Your own site
<a href="https://agentmods.dev/skills/nwave-ai/nwave/nw-sd-case-studies"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-sd-case-studies.svg" alt="Measured on agentmods" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,865 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.02865
Opus 5 $0.00020 $0.01432
Sonnet 5 $0.00008 $0.00573
Haiku 4.5 $0.00004 $0.00286

Measured yesterday against content hash fe998efd26c5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

nw-sd-case-studies scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

nWave/skills/nw-sd-case-studies/SKILL.md · 110 lines

How it starts

The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.

System Design Case Studies

Reference catalog of 25 real-world designs. Use when designing a similar system or needing precedent for architectural decisions.


Volume 1 Case Studies

Rate Limiter

Scale: API gateway middleware | Core: Token Bucket (industry standard) or Sliding Window Counter | Storage: Redis counters with TTL | Distributed: Lua scripts for atomic increment | Key insight: cross-cutting concern, belongs in middleware/gateway | Headers: 429 + Retry-After + X-RateLimit-Remaining

Consistent Hashing

Core: hash ring 0 to 2^32-1, servers at positions, keys walk clockwise | Virtual nodes: 100-200 per server, reduces load deviation from ~40% to ~5% | Used in: DynamoDB, Cassandra, Akamai, Discord | Key insight: never deploy without virtual nodes

Key-Value Store (Dynamo-style)

Core: consistent hashing for partitioning, N replicas on clockwise nodes, quorum W+R>N | Conflict: vector clocks, LWW, app-level merge | Failures: sloppy quorum + hinted handoff (temp), Merkle trees + anti-entropy (permanent), gossip for detection | Write path: WAL -> memtable -> SSTable (LSM-tree) | Read path: memtable -> Bloom filter -> SSTable(s)

Unique ID Generator

Winner: Snowflake -- 64-bit, sortable, minimal coordination | [1 unused | 41 timestamp | 5 DC | 5 machine | 12 sequence] ~4M IDs/sec/DC | Weakness: clock sync (NTP) | Alt: UUID (128-bit, not sortable), ticket server (SPOF)

URL Shortener

Scale: 100M/day ~ 1,160 QPS write, 11,600 read | Short URL: base62 with 7 chars = 3.5T combinations | Approaches: hash + collision resolution | base62 from auto-increment ID | pre-generated key service | Redirect: 301 (cached, no analytics) vs 302 (every click tracked) -- most use 302 | Key: caching critical (heavy-tailed distribution)

Web Crawler

Scale: 1B pages/month ~ 400 pages/sec, 500TB storage/month | Core: URL Frontier with priority queues (importance) + politeness queues (per-domain rate limit) | Dedup: SHA-256 exact, simhash/MinHash near-duplicate | Traps: URL length limit, max depth, blacklist | Key insight: URL frontier is the most important component

Read the full file on GitHub · 110 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 110 lines · 40 tokens per session scan A fe998efd26c5

Subscribe to this mod's changes

nw-sd-case-studies is a skill published in the GitHub repository nWave-ai/nWave (608 stars, last pushed 2d ago), licensed MIT. It adds 40 tokens to every session and 2,865 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-06.

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