Architecture

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:

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.

For each relevant category, define concrete targets:

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

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:

3. Technical Debt Register:

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:

• 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

If any check fails — fix the deliverable before presenting.

6. Engineering Estimates

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

• 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)