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Agent skill

System Design Interview

by mohitagw15856 in mohitagw15856/pm-claude-skills

Structure a complete system design answer for interview questions or real architecture sessions.

MITAuto-check passedBusiness, Finance & HR

Install System Design Interview

skills CLI
$ npx skills add mohitagw15856/pm-claude-skills --skill system-design-interview -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mohitagw15856/pm-claude-skills system-design-interview --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/system-design-interview .claude/skills/system-design-interview && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
system-design-interview
GitHub stars
1.4k
Token cost
~1.7k tokens
SKILL.md length
809 words
Files
1
Skills in repo
1,348
Repo updated
First seen
Licence
MIT

At a glance

Structure a complete system design answer for interview questions or real architecture sessions.

  • Works in 10 steps: Clarifying Questions → Functional Requirements → Non-Functional Requirements → …
  • Asked to design a system
  • SKILL.md covers Required Inputs, Output Format, Quality Checks and Anti-Patterns, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

System Design Interview is an agent skill from mohitagw15856/pm-claude-skills. Structure a complete system design answer for interview questions or real architecture sessions. Use when asked to design a system, answer a system design interview question, or architect a solution at scale. Produces a structured answer covering requirements, capacity estimates, high-level design, component deep-dives, trade-offs, and follow-up considerations.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Business, Finance & HR, covering Interview preparation and Software architecture. The repository describes itself as: 1255 professional Agent Skills for Claude, ChatGPT, Gemini, Cursor & Codex — PRDs, postmortems, leases, medical bills, layoffs, go-bags, new countries. Plain markdown, MIT, in… The licence is MIT.

When your agent uses it

  • Asked to design a system
  • Answer a system design interview question
  • Architect a solution at scale

Example prompts

  • “/system-design-interview”

Workflow steps

10 steps, taken from the step headings in SKILL.md.

  1. Clarifying Questions
  2. Functional Requirements
  3. Non-Functional Requirements
  4. Capacity Estimation
  5. High-Level Architecture
  6. Component Deep-Dive
  7. Data Flow
  8. Scaling Bottlenecks and Mitigations
  9. Trade-offs and Alternatives
  10. Follow-up Considerations

What it can do on your machine

Read from SKILL.md and the folder at commit 1cbf1f0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

System Design Interview loads about 1.7k tokens when it runs. Until then it costs about 97 tokens; SKILL.md has 809 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~97
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from mohitagw15856/pm-claude-skills at commit 1cbf1f0, republished under its MIT licence (© mohitagw15856). 809 words, ~1,673 tokens.

Download SKILL.mdSave it as .claude/skills/system-design-interview/SKILL.md (or your agent's skills folder).
name
system-design-interview
description
Structure a complete system design answer for interview questions or real architecture sessions. Use when asked to design a system, answer a system design interview question, or architect a solution at scale. Produces a structured answer covering requirements, capacity estimates, high-level design, component deep-dives, trade-offs, and follow-up considerations.

System Design Interview Skill

Structures a complete, interview-grade system design response — covering clarifying questions, requirements, capacity estimates, architecture, component design, and trade-offs. Works equally well for real architecture sessions.

Required Inputs

Ask for these if not provided:

  • The system to design (e.g. "design a URL shortener", "design a notification service", "design Twitter's feed")
  • Scope (interview prep / real architecture decision / practice run)
  • Scale target (rough numbers: DAU, requests/sec, data volume — or "assume typical web scale")
  • Constraints or priorities (e.g. prioritise availability over consistency, minimise cost, low-latency reads)
  • Time available (interview context only: 30 / 45 / 60 minutes — skip for real architecture sessions)
  • Emphasis (optional — any area to go deeper on, e.g. "focus on the DB design" or "spend more time on scaling")

Output Format

1. Clarifying Questions

Before designing, list 4–6 questions that would change the design. Examples:

  • Read-heavy or write-heavy? (affects caching and DB choice)
  • Global or single-region? (affects latency requirements)
  • Strong or eventual consistency? (affects storage and replication)
  • Acceptable latency targets? (p50 / p99)
  • Any existing infrastructure constraints?

Then proceed with stated assumptions if answering an interview question.

2. Functional Requirements

Core features (must have):

  • [Feature 1]
  • [Feature 2]
  • [Feature 3]

Out of scope (for this design):

  • [What's deliberately excluded and why]
3. Non-Functional Requirements
RequirementTarget
Availability[e.g. 99.9% / 99.99%]
Latency[e.g. p95 < 100ms for reads]
Throughput[e.g. 10k writes/sec peak]
Consistency[Strong / Eventual]
Durability[e.g. 99.999% — no data loss]
4. Capacity Estimation

Traffic:

  • DAU: [X]
  • Reads/sec: [X] (peak: [X])
  • Writes/sec: [X] (peak: [X])

Storage:

  • Per record size: [X bytes]
  • Records per day: [X]
  • 5-year storage: [X GB/TB]

Bandwidth:

  • Inbound: [X MB/s]
  • Outbound: [X MB/s]
5. High-Level Architecture

Draw an ASCII diagram specific to this system. Do not default to the client→CDN→LB→API→Cache→DB template unless it genuinely applies. Label each component with the specific technology chosen (e.g. "Kafka" not "Message Queue", "PostgreSQL" not "DB"). Describe each component in 1–2 sentences explaining its role and why that technology was chosen.

6. Component Deep-Dive

Pick the 2–3 most critical/interesting components and go deep:

[Component 1: e.g. Database Layer]

  • Choice: [Technology and why — e.g. PostgreSQL for ACID guarantees, Cassandra for write throughput]
  • Schema design (high-level): [Key tables/collections and their structure]
  • Indexing strategy: [What gets indexed and why]
  • Replication: [Primary-replica / Multi-primary — and why]

[Component 2: e.g. Caching Strategy]

  • Cache type: [Redis / Memcached — and why]
  • What gets cached: [Hot data — e.g. user sessions, frequent reads]
  • Cache invalidation: [TTL / Write-through / Write-behind — trade-offs]
  • Cache hit rate target: [e.g. 95%]

[Component 3: e.g. API Design]

  • Key endpoints: [List the 3–5 most important API calls]
  • Authentication: [JWT / OAuth / API keys]
  • Rate limiting: [Where and at what rate]
7. Data Flow

Walk through the two most critical paths end-to-end:

Write path: [Step 1 → Step 2 → Step 3...] Read path: [Step 1 → Step 2 → Step 3...]

8. Scaling Bottlenecks and Mitigations
BottleneckMitigation
[e.g. DB write throughput][e.g. sharding by user_id, write batching]
[e.g. Hot-key cache misses][e.g. local in-process cache, probabilistic early expiry]
[e.g. Single region latency][e.g. multi-region deployment, GeoDNS routing]
Show full SKILL.md (318 more words)Show less
9. Trade-offs and Alternatives

Be explicit about what was chosen and what was sacrificed:

DecisionWhyTrade-off
[e.g. Eventual consistency][Higher availability, lower latency][Stale reads possible]
[e.g. SQL over NoSQL][Complex queries, ACID transactions][Harder to shard horizontally]
[e.g. Async processing via queue][Decoupled, more resilient][Eventual delivery, harder to debug]
10. Follow-up Considerations

Things to tackle in production but out of scope for this design session:

  • Monitoring and alerting (what metrics matter)
  • Disaster recovery and backup strategy
  • Security (auth, encryption at rest/transit, rate limiting)
  • Cost optimisation at scale
  • Gradual rollout and feature flagging

Quality Checks

  • Clarifying questions are design-changing (not generic filler)
  • Capacity estimates show the arithmetic: DAU → requests/day → requests/sec → storage per record → total storage, so the numbers can be sanity-checked
  • Every row in the Trade-offs table has a non-empty Trade-off column (no rows where the trade-off is blank or says "none")
  • At least 2 component deep-dives with technology choices justified
  • Trade-offs section is honest (not just benefits of chosen approach)
  • Data flow is described end-to-end for the critical path

Anti-Patterns

  • Do not jump to solutions before clarifying requirements — always establish functional and non-functional requirements first
  • Do not present a design without discussing trade-offs — every architecture decision has costs and benefits that must be acknowledged
  • Do not use vague capacity estimates — show the actual calculation (QPS, storage bytes, bandwidth) not just "this handles scale"
  • Do not design for unlimited scale by default — match the design to the requirements stated
  • Do not skip the data model — a system design without entity definitions and data flow is incomplete

Usage Examples

  • "Help me answer a system design interview: [question]"
  • "Design [system] for a system design interview"
  • "How would I architect [system] at scale?"
  • "I have a system design interview — the question is [X]"
  • "Design a [URL shortener / chat system / notification service / feed]"

Example Trigger Phrases

  • "Design a system."
  • "Answer a system design interview question."
  • "Architect a solution at scale."

© mohitagw15856, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/system-design-interview of mohitagw15856/pm-claude-skills.

Open the folder on GitHubat commit 1cbf1f0

Compare with similar skills

System Design Interview next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

System Design Interview compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
System Design Interview this skillmohitagw15856/pm-claude-skills1.4k—~1.7kAutomated safety check: PassMIT
System Design Interview CoachingHoangNguyen0403/agent-skills-standard571—~1.3kAutomated safety check: PassMIT
Algo Senseikaranb192/algo-sensei286—~1.7kAutomated safety check: PassMIT
Backend and Agent Project Selectorlishuangqiang/backend-agent-resume-scout349—~1.4kAutomated safety check: PassApache-2.0
Leetcode Pywislertt/leetcode-py142—~1.4kAutomated safety check: PassApache-2.0
Java Backend InterviewerSnailclimb/interview-guide3.3k—~132Automated safety check: PassAGPL-3.0

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Categories

Questions about System Design Interview

What does System Design Interview do?

Structure a complete system design answer for interview questions or real architecture sessions. System Design Interview is an agent skill from mohitagw15856/pm-claude-skills. Structure a complete system design answer for interview questions or real architecture sessions.

When should I use System Design Interview?

System Design Interview fits situations like: asked to design a system; answer a system design interview question; architect a solution at scale.

How do I install System Design Interview in Claude Code?

Run `npx skills add mohitagw15856/pm-claude-skills --skill system-design-interview -a claude-code`. Or copy the skill folder (skills/system-design-interview in mohitagw15856/pm-claude-skills) into .claude/skills/system-design-interview in your project. Claude Code loads it when a task matches its description.

How do I install System Design Interview in Codex?

Run `npx skills add mohitagw15856/pm-claude-skills --skill system-design-interview -a codex`. Or copy the skill folder (skills/system-design-interview in mohitagw15856/pm-claude-skills) into .agents/skills/system-design-interview in your project. Codex loads it when a task matches its description.

Can I use System Design Interview in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mohitagw15856/pm-claude-skills --skill system-design-interview -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/system-design-interview, .gemini/skills/system-design-interview, .github/skills/system-design-interview and .opencode/skills/system-design-interview in your project.

What does System Design Interview need to run?

SKILL.md names no scripts, command-line tools or credentials: System Design Interview is instructions for the agent only.

Does System Design Interview access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is System Design Interview safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does System Design Interview use?

System Design Interview is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does System Design Interview use?

About 1.7k tokens (SKILL.md is roughly 6.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to System Design Interview?

Skills that share tags, products or a category with System Design Interview: System Design Interview Coaching (HoangNguyen0403/agent-skills-standard, 571 stars), Algo Sensei (karanb192/algo-sensei, 286 stars), Backend and Agent Project Selector (lishuangqiang/backend-agent-resume-scout, 349 stars) and Leetcode Py (wislertt/leetcode-py, 142 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains System Design Interview?

mohitagw15856 (a GitHub user) maintains it in mohitagw15856/pm-claude-skills, which has 1,433 GitHub stars. The repository holds 1,348 skills in this directory. The repository was last updated on October 8, 2026.

Source: mohitagw15856/pm-claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.