architecture

Architecture workflow — produce architectural documentation (ARD, design docs, API contracts, C4 diagrams, ARCHITECTURE.md updates) from a feature PRD, analysis request, or architectural initiative. R

SKILL.md

GitHub

Architecture

Produce architecture deliverables from a feature PRD, module/service analysis request, or architectural initiative. This workflow creates documentation — no code is written here. Output feeds into plan skill and feature-dev skill for implementation.

1. Receive Input and Classify Scope

Gather the input from the user and classify the type of work:

  • Accepted inputs: Feature PRD, architecture analysis request, technical initiative brief, verbal description
  • Read every provided document thoroughly

Scope Classification

Determine scope type based on the input:

Scope Type Trigger Primary Role Deliverables
Feature Design PRD, feature request, new capability solution-architect role ARD, API contracts, data models, sequence diagrams, NFR spec
Architecture Analysis "analyze service X", "document architecture of Y" system-architect role ARCHITECTURE.md, C4 diagrams, component map, tech debt register
Cloud Architecture Cloud infra design, landing zones, migration, multi-cloud, networking, cost cloud-architect role Cloud architecture doc, networking diagrams, cost model, DR plan
CI/CD Architecture Pipeline design, deployment strategy, GitHub org, platform engineering devops-architect role CI/CD architecture doc, pipeline diagrams, DORA targets, governance
Architecture Evolution "migrate to X", "redesign Y", tech debt initiative Multiple ARD + ARCHITECTURE.md updates, migration plan, fitness functions

If the input spans multiple scope types — execute the corresponding sections for each. If ambiguous — ask the user to clarify.

Extract Context

From the input, extract and organize:

  • Goal: What architectural problem we are solving (1–2 sentences)
  • Scope boundary: Which services, modules, or system areas are affected
  • Stakeholders: Who consumes the deliverables (engineering, product, ops)
  • Constraints: Timeline, compatibility, regulatory, team capacity
  • Non-goals: What is explicitly out of scope

If the input is incomplete — ask before proceeding. Do not assume missing requirements.

2. Understand Current Architecture

Before designing anything, map the existing state.

2a. Read Architecture Documentation

Read the following files (if they exist):

  1. ARCHITECTURE.md — system overview, component boundaries, data flow, deployment topology
  2. AGENTS.md (root) — tech stack, project structure, conventions
  3. Subdirectory AGENTS.md files — per-service/module context
  4. Existing ADRs — docs/adr/, docs/architecture/, or similar directories
  5. API specs — OpenAPI files, Protobuf definitions, GraphQL schemas

2b. Scan Affected Areas

If documentation is incomplete or absent:

// turbo
find . -name "ARCHITECTURE.md" -o -name "*.openapi.*" -o -name "*.proto" -o -name "docker-compose*" -o -name "*.tf" | head -30

Map:

  • Service boundaries: What services/modules exist, their responsibilities
  • Communication patterns: REST, gRPC, events, shared DB, message queues
  • Data stores: Databases, caches, queues — types, ownership
  • External integrations: Third-party APIs, identity providers, payment systems
  • Deployment topology: How services are deployed, scaled, networked

2c. Build Context Map

## Current Architecture Context

| Component | Tech Stack | Owner | Relevant to Scope |
|---|---|---|---|
| [service/module] | [lang + framework] | [team/role] | [yes/no — how] |

## Existing Decisions
- ADR-NNN: [title] — [status] — [relevance to current work]

## Gaps Identified
- [missing documentation, undocumented decisions, stale diagrams]

3. Define Non-Functional Requirements

Apply solution-architect role.

NFRs must be defined before any design work begins. Skip this step only for pure analysis scope.

<nfr_specification>

For each relevant category, define concrete targets:

Category Specification
Availability SLO target (e.g., 99.9%), redundancy, failover strategy
Latency p50/p95/p99 budgets per endpoint or operation
Scalability Expected load, scaling strategy (horizontal/vertical), limits
Cost Per-request/per-operation budgets, infrastructure cost bounds
Security Auth requirements, data classification, compliance (GDPR, SOC2)
Observability Tracing, logging, metrics requirements, alerting thresholds
Data Retention, consistency model (strong/eventual), backup/recovery RPO/RTO

Only include categories relevant to the scope. Omit categories that add no signal.

</nfr_specification>

Present NFRs to the user for validation before proceeding.

4. Architecture Design

Route to the appropriate section(s) based on scope type from Step 1.

4a. Feature Design → solution-architect role

For feature-level design (PRD input), produce deliverables in this order:

1. Options Analysis — Propose 2–3 design options with trade-offs:

## Option [N]: [Name]
- **Approach**: [Description]
- **Pros**: [List]
- **Cons**: [List]
- **Risk**: [High/Med/Low] — [why]
- **Effort**: [S/M/L/XL]
- **NFR impact**: [How it affects availability, latency, cost, etc.]

2. Architecture Decision Record (ARD/ADR) — Status, Context (problem + constraints), Decision (selected option + rationale), Consequences (positive/negative/neutral), Alternatives Considered.

3. Detailed Design:

  • C4 diagrams (Mermaid) — Context and/or Container level showing the feature's impact
  • Sequence diagrams — for multi-service interactions, async flows
  • API contracts — new or modified endpoints (OpenAPI fragments or structured tables)
  • Data models — new entities, schema changes, migration strategy
  • Error handling — failure modes, retry strategy, degradation behavior

4. Security Review:

  • Threat scenarios (3–5 concrete abuse cases)
  • Auth/authz design for new endpoints
  • Data protection requirements (PII, encryption, access control)

4b. Architecture Analysis → system-architect role

For analysis scope, produce:

1. Architecture Assessment:

  • C4 diagrams (Context + Container level) of current state
  • Component inventory with responsibilities, tech stack, dependencies
  • Data flow diagrams for critical paths
  • Integration point map (sync/async, contracts, SLAs)

2. Gap Analysis:

Area Current State Desired State Gap Priority
[area] [what exists] [what should exist] [delta] High/Med/Low

3. Technical Debt Register:

Item Impact Effort Priority Recommendation
[debt item] High/Med/Low S/M/L/XL [rank] [action]

4. ARCHITECTURE.md Update — create or update following templates/architecture.template.md.

4c. Architecture Evolution → Both Roles

For migration/evolution initiatives, produce both:

  • ADR (from 4a) documenting the migration decision
  • ARCHITECTURE.md update (from 4b) showing target state
  • Migration plan: phased approach (strangler fig, expand-contract, branch by abstraction)
  • Fitness functions: automated architectural checks to enforce during transition
  • Rollback strategy: how to revert if migration fails at each phase

5. Quality Gates

Review all deliverables against the checklist:

<quality_checklist>
  • NFRs are concrete (numbers, not "should be fast")
  • Every decision has documented rationale and alternatives
  • Diagrams match the described architecture (no stale diagrams)
  • API contracts are complete (request, response, errors, auth)
  • Data models include migration strategy for schema changes
  • Security review covers OWASP Top 10 (+ LLM Top 10 for AI systems)
  • Backward compatibility is preserved or migration path documented
  • Observability requirements defined (traces, logs, metrics, alerts)
  • No contradictions with existing ADRs or ARCHITECTURE.md
  • Cost impact estimated for infrastructure/service changes
</quality_checklist>

If any check fails — fix the deliverable before presenting.

6. Engineering Estimates

For feature design scope, produce estimates to feed plan skill:

Component Task Complexity Role
[component] [task description] S / M / L / XL role-id
  • Critical path: Longest dependency chain (e.g., DB Migration → Backend API → Frontend → E2E Tests)
  • Parallelization: Which tasks can run concurrently by different roles
  • Constraints: Hard dependencies on external teams, services, or decisions
  • Risks: Dependency/integration risks with mitigations

Skip this step for pure analysis scope.

7. Present Deliverables

Compile and present: scope summary, deliverables table (document/type/status), key decisions with rationale, risk table (risk/impact/mitigation), and next steps (stakeholder review → plan skill → feature-dev skill).

Wait for user review. The user may request changes, additional analysis, or approve.

8. Persist Artifacts

After approval, save deliverables to the project:

  1. ADRs → docs/adr/ or docs/architecture/decisions/ (create dir if missing)
  2. Design docs → docs/architecture/ or docs/design/
  3. API contracts → alongside existing API specs or in docs/api/
  4. ARCHITECTURE.md → project root (update existing or create new)

For each file:

  • Use consistent naming: ADR-NNN-[kebab-case-title].md, [feature]-design.md
  • Verify file was created successfully

If the project has no established docs/ structure — propose one and confirm with user.

9. Handoff

Guide the next steps based on scope:

  • Feature Design → Run plan skill with the produced ARD and design docs as input
  • Architecture Analysis → Share findings with stakeholders. If action items identified — create tickets or run plan skill for each initiative
  • Architecture Evolution → Run plan skill for each migration phase

Integration

  • Input from: product skill (PRD output), plan skill (architecture questions during planning), direct analysis requests
  • Followed by: plan skill (work decomposition), feature-dev skill (implementation)
  • Roles: solution-architect role (feature design, ADRs, API contracts), system-architect role (system analysis, ARCHITECTURE.md, component boundaries), cloud-architect role (cloud platform design, landing zones, networking, cost), devops-architect role (CI/CD architecture, deployment strategies, platform engineering)
  • Templates: templates/architecture.template.md (ARCHITECTURE.md structure)
  • Skills: context-engineering skill (for AI/agent system architecture)