system-design

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This skill should be used when the user asks to "design a system", "design <a product>" (e.g. "design WhatsApp", "design a URL shortener", "design a news feed"), "high-level architecture for…", "how would you architect…", "system design interview", or wants to scope, diagram, and justify a backend/distributed-system design. It runs a reasoning loop — clarify, estimate, design, weigh trade-offs, stress-test, iterate — and routes to focused building-block skills. Use it whenever a request is an open-ended design problem, even if the user doesn't say "system design".

proyecto26 By proyecto26 schedule Updated 6/2/2026

name: system-design description: This skill should be used when the user asks to "design a system", "design " (e.g. "design WhatsApp", "design a URL shortener", "design a news feed"), "high-level architecture for…", "how would you architect…", "system design interview", or wants to scope, diagram, and justify a backend/distributed-system design. It runs a reasoning loop — clarify, estimate, design, weigh trade-offs, stress-test, iterate — and routes to focused building-block skills. Use it whenever a request is an open-ended design problem, even if the user doesn't say "system design".

System Design (orchestrator)

Drive an open-ended design problem from a vague prompt to a justified, stress-tested architecture — by reasoning, not by recalling a diagram. This skill owns the method and the routing; the actual component recipes live in focused building-block skills it pulls in as needed.

The single most important idea, from which everything here follows:

Do not memorize architectures; learn the forces that shape them. There is no single correct solution — success depends on the assumptions you make explicit.

A design that works for 1,000 users may fail at 1,000,000. Treat every architecture as a hypothesis that holds until a constraint changes, and be ready to redraw it calmly when one does.

The reasoning loop

Work this loop out loud. It is a loop, not a checklist — late steps routinely send you back to early ones, and that is the point.

  1. Clarify requirements — turn the vague prompt into functional requirements, non-functional constraints, and an explicit out of scope. Scope to a few core features; say so. → skill requirements-scoping
  2. Estimate scale — back-of-the-envelope QPS, storage, bandwidth, read/write ratio. Numbers decide the design; "high traffic" does not. → skill back-of-the-envelope
  3. Propose a high-level design — sketch the boxes and arrows (clients, LB, services, stores, caches, queues, CDN) and the user-facing API. Get buy-in before going deep. → skill api-design, plus the building blocks below.
  4. Evaluate trade-offs — for every major choice, state what it solves, what it worsens, and what would make you change it. Never name a tool without this. → reference tradeoff-framework.md
  5. Stress-test failure modes — find single points of failure, decide the degradation story, plan recovery. Assume every component breaks. → skill resilience-failure
  6. Iterate / deep-dive — pick the most interesting or fragile component and go deep; let new constraints ("what if writes 10×?", "lose a region?") drive a redesign of the affected part.

These six steps are the same four activities the GUIDE names — ask refining questions → handle the data → discuss components → discuss trade-offs — with estimation and failure-testing made explicit. See references/reasoning-loop.md for the full walk-through and time budgeting.

Routing to building blocks

This plugin is a wiki of composable parts. As each concern comes up in the loop, invoke the focused skill (via the Skill tool) rather than reconstructing its recipe from memory — load it so the options, trade-off table, behavior under stress, and cloud-provider variants come from the skill itself. That invocation is how composition works at runtime: a bare skill name below is a skill to trigger, not a file to read. Invoke each as its concern becomes active:

When the problem turns to… Use skill
What features / constraints / scope? requirements-scoping
How many QPS, how much storage, how many servers? back-of-the-envelope
Endpoints, request/response, pagination, idempotency api-design
Monolith vs microservices, service boundaries, gateway, discovery service-decomposition
SQL vs NoSQL, schema, indexing, sharding, replication data-storage
What to cache, eviction, invalidation, hot keys caching
Distributing traffic, L4/L7, health checks load-balancing
Async work, queues vs streams, delivery guarantees messaging-streaming
CAP, consistency models, quorum, consensus, hashing consistency-coordination
Fault tolerance, circuit breakers, degradation, rate limiting resilience-failure
Static/media delivery, edge, geo-routing content-delivery
How the design evolves with 10×/100× growth scaling-evolution
How clients resolve the service, geo/failover routing dns
Unique IDs at scale (Snowflake/UUID/ticket) sequencer
Storing large/unstructured objects (images, video, files) blob-store
Metrics/logs/traces, health checks, SLOs, alerting observability
High-volume log collection/shipping/retention distributed-logging
Full-text search, inverted index, autocomplete distributed-search
Background / scheduled / recurring jobs task-scheduling
Counting likes/views at huge write rates sharded-counters
Drawing/visualizing the architecture architecture-diagram

Full descriptions, the bottom-up layering, and "which block answers which question" are in references/building-blocks-index.md (the canonical 21-block catalog). Trigger a block directly when the user asks about just that part — the orchestrator is not required for every question.

Guardrails: the ways designs fail

The GUIDE catalogs ten failure modes. They are not about wrong answers; they are about wrong signals. Keep these reflexes (full list and antidotes in references/failure-modes.md):

  • Clarify before designing. Rushing to a solution signals memorization.
  • Quantify before choosing. Convert "heavy traffic" into numbers first.
  • Justify every component. Three questions per choice: solves / worsens / when-to-change. "Industry standard" is not a justification.
  • Open building blocks, don't name them. Know how a cache, queue, or DB behaves under stress — not just what it is called.
  • Design for failure. "Add more retries" usually amplifies an outage.
  • Make interfaces concrete. If you can't write the request, response, and primary key, the diagram is guesswork.
  • Treat the architecture as a hypothesis. If a small constraint change collapses the whole design, it was memorized, not reasoned.

Collaborate; do not present

A design discussion is a working session, not a lecture. Propose, invite the critique, and adapt in real time. When a constraint changes, name which earlier assumption it invalidates and redesign that part — defending a sunk design is a worse signal than a flawed first idea. See references/collaboration-playbook.md for how to narrate, handle curveballs, and pivot.

When requirements are genuinely ambiguous and the answer changes the design, ask the user a clarifying question rather than guessing silently.

Producing the design

  • Capture scope in assets/requirements-template.md (functional / non-functional / out-of-scope / assumptions).
  • Write up the design with assets/design-doc-template.md — it threads the reasoning loop, so the trade-offs and failure story are first-class, not footnotes.
  • Diagram with the in-plugin architecture-diagram skill — a self-contained dark-theme HTML+SVG generator that ships in this plugin (no external dependency). A quick ASCII sketch is fine for early thinking; render properly once the design is clear. See references/diagramming.md for what to draw at each step and how to specify a diagram to that skill.
  • Persist it so the work survives the conversation: write the requirements and design doc to a file (suggest docs/design/<system>.md; ask the user where if unsure). Keep trade-off exploration and constraint back-and-forth in the conversation; commit the settled artifacts (scope, design, key decisions, data model, diagram) to the file.
  • Score & diagnose before wrapping: rate the design with the quality bar and run the Quick Diagnostic in references/failure-modes.md, and state the weakest dimension + what would raise it.

Running it as a workflow

Two entry points drive this skill as a repeatable process:

  • /design <system> — the slash command that runs the full loop on a problem.
  • system-design-orchestrator — the agent the command dispatches to; it loads this skill, then invokes the building-block skills as each concern arises.

Both compose the same blocks listed above — invoke a block skill when its concern is active rather than reconstructing its recipe from memory.

References

  • references/reasoning-loop.md — the six-step loop in depth, with the news-feed walk-through and 45-minute time budget. Read when running a full design.
  • references/failure-modes.md — the ten failure modes and their antidotes. Read to self-check a design or diagnose why one isn't landing.
  • references/tradeoff-framework.md — the solves/worsens/when-to-change method and common axis trade-offs (latency↔throughput, consistency↔availability, cost↔complexity). Read at step 4.
  • references/building-blocks-index.md — the full wiki index: every block, what it answers, and how blocks combine. Read to route.
  • references/collaboration-playbook.md — narrating, handling curveballs, pivoting on constraint changes. Read when the discussion gets adversarial.
  • references/diagramming.md — what to draw at each loop step and how to specify a diagram to the architecture-diagram skill. Read when drawing.
  • references/worked-example-news-feed.md — one end-to-end pass of the loop, shown as reasoning (not a template to memorize).

Assets

  • assets/requirements-template.md — functional / non-functional / scope / assumptions capture.
  • assets/design-doc-template.md — a design write-up structured around the reasoning loop.