What makes System Design notable?

1.9K downloads. Trust evidence available

How should System Design be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

System Design

Deep system design workflow—requirements, capacity, APIs, data, consistency, failure modes, trade-offs, and evolution. Use when preparing interviews, RFCs, g... Skill: System Design Owner: mikeclaw007 Summary: Deep system design workflow—requirements, capacity, APIs, data, consistency, failure modes, trade-offs, and evolution. Use when preparing interviews, RFCs, g... Tags: latest:1.0.0 Version history: v1.0.0 | 2026-03-24T15:51:02.209Z | auto - Initial release of the "system-design" skill providing a structured, seven-stage system design workflow. - Guides users through req

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.9k

Updated

Oct 9, 2026

Version

1.0.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.9K downloads reported by the source. Last updated 10/9/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 9, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 9, 2026
Adoption signal: 1.9K downloadsadoption · observed Oct 9, 2026
Latest release: 1.0.0release · observed Mar 24, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s173n2mnssqbs3ebpdz3b52ssh83gshx:system-design

Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-mikeclaw007-system-design/snapshot"

Documentation

CLAWHUB

8,174 characters of source documentation, loaded on request.

Extracted files

3 files captured from the source.

SKILL.md

---
name: system-design
description: Deep system design workflow—requirements, capacity, APIs, data, consistency, failure modes, trade-offs, and evolution. Use when preparing interviews, RFCs, greenfield systems, or major redesigns (microservices, multi-region, real-time).
---

# System Design (Deep Workflow)

System design is **structured decision-making** under constraints. The output is not a diagram—it is **clarity on requirements**, **explicit trade-offs**, and a **path to evolve** when load and features change.

## When to Offer This Workflow

**Trigger conditions:**

- “Design Twitter/Instagram/WhatsApp” (interview style)
- Greenfield service, major scale milestone, multi-region, or realtime needs
- Refactoring monolith—**boundaries** and **data ownership** questions

**Initial offer:**

Use **seven stages**: (1) clarify requirements, (2) capacity & SLO sketch, (3) high-level architecture, (4) data model & storage, (5) APIs & traffic patterns, (6) reliability & failure modes, (7) trade-offs & evolution. Ask **interview mode** (time-boxed) vs **real project** (depth).

---

## Stage 1: Clarify Requirements

**Goal:** **Functional** and **non-functional** requirements explicit.

### Functional

- Core **user actions**; **read vs write** ratio; **search**, **ranking**, **notifications**?

### Non-functional

- **Scale**: DAU, QPS, data size, growth—orders of magnitude OK if unknown
- **Latency**: p95/p99 targets; sync vs async acceptable?
- **Consistency**: can reads be stale? global ordering needed?
- **Durability**: loss tolerance; audit; compliance

### Out of Scope

- Explicitly list **non-goals** to prevent scope creep in interviews and real life

**Exit condition:** **Problem statement** one paragraph; **constraints** bullet list.

---

## Stage 2: Capacity & SLO Sketch

**Goal:** **Back-of-envelope** math to sanity-check bottlenecks.

### Rough math

- Requests/day → QPS peak with **3–10×** factor if needed
- Storage/day; **replication** multiplier
- **Bandwidth** for large payloads (images, video)

### SLO mindset

- **Availability** vs **cost**; **strong consistency** vs **latency**

**Exit condition:** Identified **likely bottleneck** class: DB, network, fan-out, storage.

---

## Stage 3: High-Level Architecture

**Goal:** Boxes and arrows with **reasons**.

### Typical layers

- **Clients** → **LB/API** → **services** → **caches/queues** → **databases/object storage**
- **CDN** for static and cacheable API responses when applicable
- **Async** processing for heavy work (indexing, emails, ML)

### Principles

- **Separation** of read/write (CQRS) only when justified by scale
- **Idempotent** workers; **at-least-once** messaging assumptions

**Exit condition:** Diagram + **why not simpler** (monolith) answered in one paragraph.

---

## Stage 4: Data Model & Storage

**Goal:** Choose **stores** for access patterns, not buzzwords.

### Questions

- **Relational** vs **document** vs **wide-column** vs **graph**—**query patterns** firs

_meta.json

{
  "ownerId": "kn736js06krgvrxx1g1jkqw0h9831z63",
  "slug": "system-design",
  "version": "1.0.0",
  "publishedAt": 1774367462209
}

skill-card.md

## Description:

Deep system design workflow covering requirements, capacity, APIs, data, consistency, failure modes, trade-offs, and evolution for interviews, RFCs, greenfield systems, and major redesigns.

This skill is ready for commercial/non-commercial use.

## Publisher:

[mikeclaw007](https://clawhub.ai/user/mikeclaw007)

### License/Terms of Use:

MIT-0

## Use Case:

Developers, engineers, and technical interview candidates use this skill to structure system design discussions from requirements through capacity planning, architecture, data modeling, APIs, reliability, trade-offs, and evolution.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: The skill provides broad system design guidance that could be applied to architecture decisions without project-specific validation.

Mitigation: Review recommendations against the target system's requirements, constraints, SLOs, security needs, and operational context before implementation.

## Reference(s):


## Skill Output:

**Output Type(s):** [Guidance, Markdown, Analysis]

**Output Format:** [Markdown guidance with structured checklists and design prompts]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Advisory markdown only; the reviewed artifact contains no commands, data access, persistence, or hidden behavior.]

## Skill Version(s):

1.0.0 (source: release metadata)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

Github ReposUpdated 6h agoRank 70

AionUi

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

MCPOPENCLAW

Github ReposUpdated 6mo agoRank 70

activepieces

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

OPENCLAW

Github ReposUpdated 6mo agoRank 70

cherry-studio

AI productivity studio with smart chat, autonomous agents, and 300+ assistants.

MCPOPENCLAW

Github ReposUpdated 7mo agoRank 70

CopilotKit

The Frontend for Agents & Generative UI. React + Angular