Systematically evaluate architecture decisions, document trade-offs, and select appropriate patterns for context. Provides frameworks for pattern selection, ADR creation, and technical debt management.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionarchitecture-decisionExecute the skills CLI command in your project's root directory to begin installation:
Fetches architecture-decision from jwynia/agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate architecture-decision. Access via /architecture-decision in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Systematically evaluate architecture decisions, document trade-offs, and select appropriate patterns for context. Provides frameworks for pattern selection, ADR creation, and technical debt management.
Use this skill when:
Do NOT use this skill when:
Context drives decisions. No pattern is universally good or bad. The best architecture is not the most elegant—it's the one that best serves its purpose while remaining maintainable and evolvable.
Every architectural decision involves trade-offs:
| Vertex | Maximized By | Cost |
|---|---|---|
| Simplicity | Monolith, sync communication, single DB | Scalability limits |
| Flexibility | Microservices, event-driven, plugins | Complexity overhead |
| Performance | Caching, denormalization, optimized code | Maintainability |
Balance Strategies:
| Context | Preferred Patterns | Avoid |
|---|---|---|
| Small team | Monolith, vertical slices, shared DB | Microservices, complex abstractions |
| Multiple teams | Service boundaries, API contracts | Shared state, tight coupling |
| Context | Preferred Patterns | Reasoning |
|---|---|---|
| Startup | Monolith first, vertical scaling | Optimize for development speed |
| Enterprise | Service mesh, horizontal scaling | Optimize for operational scale |
| Option | Consistency | Flexibility | Scalability | Complexity | Cost | Total |
|---|---|---|---|---|---|---|
| Option A | 5 | 2 | 3 | 2 | 3 | 15 |
| Option B | 3 | 5 | 4 | 3 | 3 | 18 |
| Option C | 2 | 3 | 5 | 1 | 2 | 13 |
Weight factors based on context priorities.
# ADR-[NUMBER]: [TITLE]
## Status
[Proposed | Accepted | Deprecated | Superseded]
## Context
[What is the situation requiring a decision?]
### Requirements
- [Requirement 1]
- [Requirement 2]
### Constraints
- [Constraint 1]
- [Constraint 2]
## Decision
[What is the decision?]
### Justification
- [Reason 1]
- [Reason 2]
## Consequences
### Positive
- [Benefit 1]
- [Benefit 2]
### Negative
- [Drawback 1]
- [Drawback 2]
## Alternatives Considered
### [Alternative 1]
Reason rejected: [Why]
### [Alternative 2]
Reason rejected: [Why]
| Type | Examples | Payment Strategy |
|---|---|---|
| Design | Missing abstractions, tight coupling | Refactoring sprints |
| Code | Duplication, complexity, poor naming | Continuous cleanup |
| Test | Missing tests, flaky tests | Test improvement |
| Documentation | Missing docs, outdated diagrams | Documentation sprints |
Symptoms: No clear structure, everything depends on everything Remedy: Identify boundaries, extract modules, establish interfaces
Symptoms: Services must deploy together, sync chains, shared DBs Remedy: Merge related services, async communication, separate DBs
Symptoms: One solution for all problems, force-fitting patterns Remedy: Learn alternatives, evaluate objectively, prototype options
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
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Useful defaults in architecture-decision — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added architecture-decision from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: architecture-decision is focused, and the summary matches what you get after install.
architecture-decision fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for architecture-decision matched our evaluation — installs cleanly and behaves as described in the markdown.
architecture-decision is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
architecture-decision reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for architecture-decision matched our evaluation — installs cleanly and behaves as described in the markdown.
architecture-decision fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added architecture-decision from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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