Die Oberfläche ist lokalisiert; Skill-Beschreibungen und -Dokumente werden per KI automatisch in Ihre Sprache übersetzt. Code, Befehle, Pfade und Fachbegriffe bleiben im Original, maßgeblich ist das Dokument des Autors.
Skills entdecken
Design und Kreativität · SKILL.md

system-design-session

system-design-session

Run an interactive system design session that turns a product goal into a sized, justified architecture with diagrams, ADRs, a scorecard, and a machine-readable handoff.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill-Dokumentation

GitHub

name: system-design-session description: "Run an interactive system design session that turns a product goal into a sized, justified architecture with diagrams, ADRs, a scorecard, and a machine-readable handoff." metadata: internal: true triggers: keywords: - system design session - workflow

System Design Session Skill

[!IMPORTANT] Run an interactive system design session that turns a product goal into a sized, justified architecture with diagrams, ADRs, a scorecard, and a machine-readable handoff.

Optional args: slug=, ticket=<id/url>, mode=interactive|autonomous|channel, channel=, auto_continue=true|false, profile=business|hybrid|technical.

Instructions

When the user asks to perform this workflow, execute the following steps:

System Design Workflow (Architecture / How Big)

Goal: Produce a capacity-justified architecture baseline that design-solution can turn into contracts.

Steps

  1. Load inputs:
    • Load system-design-methodology plus matched siblings (estimation, building-blocks, data-architecture, resilience-ops, review, principles) and common-architecture-diagramming for the draw.io render pipeline, and common-decision-discipline for option cards and the evidence ledger.
    • Load PRD or ticket, existing architecture docs, and current traffic/incident data when reviewing an existing system.
  2. Classify and announce:
    • Mode: new design | review existing | interview practice.
    • Interview practice: load system-design-interview-coaching, run the seven phases on its time budget as the interviewer, score with its rubric after; steps 3-6 below are the candidate's work, not the agent's.
    • Depth: quick sketch (defaults assumed, each labeled ASSUMED) or full session (every gate confirmed).
    • Escalate quick to full when an irreversible or cross-team choice appears.
  3. Intake (gate):
    • Ask max 3 blocking questions per turn from the intake checklist; supply a recommended default for each.
    • Record functional requirements, NFR targets, out-of-scope fence, operating team, and every ASSUMED value.
    • Review-existing mode: map current state, measure real traffic and incidents, and name the binding constraint before proposing change.
  4. Estimate (gate):
    • Compute average and peak QPS, storage over retention, bandwidth, working-set memory, and monthly cost at that scale.
    • Name the shaping quantity and confirm the order of magnitude before any component is drawn.
  5. Design incrementally:
    • Price the null option first (do nothing, buy, or extend an existing service); rejecting it needs a stated reason.
    • Start from client, API, service, store; add one component at a time as constraint -> component -> cost.
    • Fix API surface, data ownership, and consistency class per flow.
    • Route the result as HLD first: record audience, scope, shaping constraint, ownership, failure domain, lifecycle status, and the decision to review. HLD may be prose or a selected context/container view; do not require every diagram.
    • For each chosen deep dive, create an LLD handoff (REQ-* -> HLD-* -> CMP-* -> LLD-* -> VER-*) covering the component contract, invariant, ordering/idempotency, failure/recovery, and verification. “Low-level design” is the same lane as LLD.
    • Render only selected views through common-architecture-diagramming when they answer named questions: use context/container, sequence, dataflow, deployment, or state as appropriate; prose or a table is sufficient otherwise. Carry metric and constraint only when stated, and leave them absent rather than inventing numbers. No doc yet (quick sketch, or writes disallowed): leave evidence absent and let the node render UNVERIFIED. Output only the selected docs/architecture/[slug]-<type>.drawio artifacts plus exported images. Phase map: system-design-methodology/references/phase-deliverables.md.
  6. Deep dive and decide:
    • Select zero, one, or multiple deep dives from the unresolved consequential risks. Each selected dive must resolve a named decision; do not impose a minimum specialist count or invent work. Brief each selected specialist with profile, audience/question, workload, SLO, team/budget, invariant, scope, evidence status, and current HLD decision.
    • Require options with rejection reasons, an LLD contract, concrete adverse timeline/recovery, verification hooks, and an ADR reversal trigger. Specialists must not re-run intake or add machinery without a constraint.
    • Merge the returned options, failure modes, and irreversible decisions; state bottlenecks, SPOFs, and rejected alternatives with reasons.
    • Write one ADR per irreversible decision, each with its reversal trigger; stage the plan as build now, enabling seam, and the metric threshold that triggers the next step.
    • Before producing independent post-decision docs/diagrams, list exact-file slices, acceptance checks, verification and integration owner; assign each bounded slice to the lowest-cost qualified configured executor where available. Keep decisions and final review with the lead.
    • Allow one focused correction for a defective slice before escalating per configured fallback; record executor/model, exception or fallback reason, corrections and available usage/cost (otherwise unavailable) in the handoff. Do not claim savings without data.
    • Save the design to docs/design/system-design-[slug].md when file writes are allowed.
  7. Score and hand off:
    • Run the nine-axis scorecard with a declared system profile; permit a justified N/A axis and do not reward caches/queues/replicas/regions without a measured need, owner, cost, and recovery behavior.
    • Run independent semantic review in system-design-review/references/semantic-evaluation.md; lexical checks remain smoke signals.
    • Emit the HLD/LLD trace and handoff payload; route to design-solution.

Runtime Contract

  • Use when architecture, scale, or store selection is unsettled and the design would otherwise be guessed.
  • Required inputs: a product goal or existing system, plus scale parameters or explicit permission to assume defaults.
  • Never emit a component set before capacity numbers exist or assumptions are labeled.
  • Return BLOCKED for undecided cross-team ownership, compliance/residency constraints, or a budget ceiling that changes the topology.

Handoff Payload

  • slug, operator_profile, design doc path, mode and depth, requirement table, capacity numbers, component list with justifications, data ownership map, NFR thresholds, diagram paths (.drawio + image), ADR list, scorecard, risk register, next workflow.

Blocking Questions

  • Ask max 3 at a time with a recommended default and 2-3 options.

Output Template

# System Design: [Name]
## Mode And Depth
## Requirements (Functional / NFR / Out Of Scope)
## Assumptions
## Capacity Estimation (incl. monthly cost)
## Null Option Considered
## Component Architecture (constraint -> component -> cost)
## Selected Views (optional; prose or tables allowed)
## Data Ownership And Consistency
## Deep Dives
## Trade-offs And Rejected Alternatives
## Staged Plan (Now / Seam / Trigger)
## ADRs (with reversal triggers)
## Design Scorecard (9 axes)
## Interview Scorecard (6 × 0-3, interview mode only)
## Risk Register

## Outcome Report
{schema_version: 1, run_id: "[run-id]", slug: "[slug]", workflow: system-design-session, feature_status: "[existing schema status supported by available design evidence; use design_ready only when requirements and proposed mechanisms are sufficient]", started_at: "[timestamp]", completed_at: "[timestamp]", requirement_trace: {brd_objectives: [], requirements: [], acceptance_criteria: [], srs: []}, completed_evidence: [], missing_evidence: [], decision_needed: [], recommended_next_workflow: design-solution, cost: {source: unavailable}, agent: {identity: "[agent-identity]", model: "[model]"}}

## Next Workflow
design-solution | plan-feature
## Cost Report
Call `get_session_cost(workflow="system-design-session")` before final handoff.
Gespeicherte Skills