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.
npx skills add ancoleman/ai-design-components --skill designing-distributed-systemsgit clone --depth 1 https://github.com/ancoleman/ai-design-componentsWrote 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.
[](https://agentmods.dev/skills/ancoleman/ai-design-components/designing-distributed-systems)<a href="https://agentmods.dev/skills/ancoleman/ai-design-components/designing-distributed-systems"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/designing-distributed-systems/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ancoleman/ai-design-components/designing-distributed-systems"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/designing-distributed-systems.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00099 | $0.03857 |
| Opus 5.5 | $0.00040 | $0.01543 |
| Sonnet 5.5 | $0.00020 | $0.00771 |
| Haiku 4.5 | $0.00010 | $0.00386 |
Grade A, and why
designing-distributed-systems 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 2mo ago.
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.
How it starts
The opening of the file, as written. The whole thing — 478 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Designing Distributed Systems
Design scalable, reliable, and fault-tolerant distributed systems using proven patterns and consistency models.
Purpose
Distributed systems are the foundation of modern cloud-native applications. Understanding fundamental trade-offs (CAP theorem, PACELC), consistency models, replication patterns, and resilience strategies is essential for building systems that scale globally while maintaining correctness and availability.
When to Use This Skill
Apply when:
- Designing microservices architectures with multiple services
- Building systems that must scale across multiple datacenters or regions
- Choosing between consistency vs availability during network partitions
- Selecting replication strategies (single-leader, multi-leader, leaderless)
- Implementing distributed transactions (saga pattern, event sourcing, CQRS)
- Designing partition-tolerant systems with proper consistency guarantees
- Building resilient services with circuit breakers, bulkheads, retries
- Implementing service discovery and inter-service communication
Core Concepts
CAP Theorem Fundamentals
CAP Theorem: In a distributed system experiencing a network partition, choose between Consistency (C) or Availability (A). Partition tolerance (P) is mandatory.
Network partitions WILL occur → Always design for P
During partition:
├─ CP (Consistency + Partition Tolerance)
│ Use when: Financial transactions, inventory, seat booking
│ Trade-off: System unavailable during partition
│ Examples: HBase, MongoDB (default), etcd
│
└─ AP (Availability + Partition Tolerance)
Use when: Social media, caching, analytics, shopping carts
Trade-off: Stale reads possible, conflicts need resolution
Examples: Cassandra, DynamoDB, Riak
PACELC: Extends CAP to consider normal operations (no partition).
- If Partition: Choose Availability (A) or Consistency (C)
- Else (normal): Choose Latency (L) or Consistency (C)
Consistency Models Spectrum
What ships with it
21 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- diagrams/caching-patterns.txt 2.3 KB
- diagrams/cap-theorem.txt 2.7 KB
- diagrams/replication-topologies.txt 1.9 KB
- diagrams/saga-flow.txt 1.3 KB
- examples/circuit-breaker/circuit_breaker.py 5.3 KB runs code
- examples/consistent-hashing/consistent_hash.py 4.5 KB runs code
- examples/cqrs/cqrs_example.py 4.7 KB runs code
- examples/event-sourcing/event_store.py 4.2 KB runs code
- examples/saga-orchestration/saga_orchestrator.py 3.9 KB runs code
- examples/service-discovery/consul_discovery.py 2.9 KB runs code
- outputs.yaml 21 KB
- references/caching-strategies.md 2.5 KB
- references/cap-pacelc-theorem.md 14 KB
- references/consensus-algorithms.md 15 KB
- references/consistency-models.md 21 KB
- references/event-sourcing-cqrs.md 6.5 KB
- references/partitioning-strategies.md 17 KB
- references/replication-patterns.md 19 KB
- references/resilience-patterns.md 6.1 KB
- references/saga-pattern.md 4.1 KB
- references/service-discovery.md 2.6 KB
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.
- 2mo ago First seen · 478 lines · 99 tokens per session scan A 6eb17cc70157
designing-distributed-systems is a skill published in the GitHub repository ancoleman/ai-design-components (527 stars, last pushed 11mo ago), licensed MIT. It adds 99 tokens to every session and 3,857 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-08-30.
designing-distributed-systems compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| designing-distributed-systemsancoleman/ai-design-components | Skill | 527 | 11mo ago | MIT | A | 99 | Claude Code |
| form-strategyrampstackco/claude-skills | Skill | 1.0k | 11d ago | MIT | A | 107 | Claude Code |
| seo-apiseranking/seo-skills | Skill | 199 | yesterday | MIT | A | 218 | Claude Code |
| mcp-server-builderOneWave-AI/claude-skills | Skill | 415 | 18d ago | MIT | A | 79 | Claude Code, Codex |
| api-endpoint-scaffolderOneWave-AI/claude-skills | Skill | 415 | 18d ago | MIT | A | 36 | Claude Code, Codex |
| netlify-developmentMindrally/skills | Skill | 297 | 29d ago | Apache-2.0 | A | 78 | Claude Code |
| apollo-graphqlMindrally/skills | Skill | 297 | 29d ago | Apache-2.0 | A | 26 | Claude Code |