Awesome-omni-skills architecture-decision-records
Architecture Decision Records workflow skill. Use this skill when the user needs Comprehensive patterns for creating, maintaining, and managing Architecture Decision Records (ADRs) that capture the context and rationale behind significant technical decisions and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
git clone https://github.com/diegosouzapw/awesome-omni-skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/architecture-decision-records" ~/.claude/skills/diegosouzapw-awesome-omni-skills-architecture-decision-records && rm -rf "$T"
skills/architecture-decision-records/SKILL.mdArchitecture Decision Records
Overview
This public intake copy packages
plugins/antigravity-awesome-skills-claude/skills/architecture-decision-records from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.
Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.
This intake keeps the copied upstream files intact and uses
metadata.json plus ORIGIN.md as the provenance anchor for review.
Architecture Decision Records Comprehensive patterns for creating, maintaining, and managing Architecture Decision Records (ADRs) that capture the context and rationale behind significant technical decisions.
Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Core Concepts, Templates, Status, Context, Decision Drivers, Considered Options.
When to Use This Skill
Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.
- Making significant architectural decisions
- Documenting technology choices
- Recording design trade-offs
- Onboarding new team members
- Reviewing historical decisions
- Establishing decision-making processes
Operating Table
| Situation | Start here | Why it matters |
|---|---|---|
| First-time use | | Confirms repository, branch, commit, and imported path before touching the copied workflow |
| Provenance review | | Gives reviewers a plain-language audit trail for the imported source |
| Workflow execution | | Starts with the smallest copied file that materially changes execution |
| Supporting context | | Adds the next most relevant copied source file without loading the entire package |
| Handoff decision | | Helps the operator switch to a stronger native skill when the task drifts |
Workflow
This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.
- Capture the decision context, constraints, and drivers.
- Document considered options with tradeoffs.
- Record the decision, rationale, and consequences.
- Link related ADRs and update status over time.
- Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
- Read the overview and provenance files before loading any copied upstream support files.
- Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
Imported Workflow Notes
Imported: Instructions
- Capture the decision context, constraints, and drivers.
- Document considered options with tradeoffs.
- Record the decision, rationale, and consequences.
- Link related ADRs and update status over time.
Imported: Review Process
#### Imported: Summary Propose adopting event sourcing pattern for the order management domain to improve auditability, enable temporal queries, and support business analytics. #### Imported: Core Concepts ### 1. What is an ADR? An Architecture Decision Record captures: - **Context**: Why we needed to make a decision - **Decision**: What we decided - **Consequences**: What happens as a result ### 2. When to Write an ADR | Write ADR | Skip ADR | |-----------|----------| | New framework adoption | Minor version upgrades | | Database technology choice | Bug fixes | | API design patterns | Implementation details | | Security architecture | Routine maintenance | | Integration patterns | Configuration changes | ### 3. ADR Lifecycle
Proposed → Accepted → Deprecated → Superseded ↓ Rejected
## Examples ### Example 1: Ask for the upstream workflow directly ```text Use @architecture-decision-records to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.
Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.
Example 2: Ask for a provenance-grounded review
Review @architecture-decision-records against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.
Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.
Example 3: Narrow the copied support files before execution
Use @architecture-decision-records for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.
Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.
Example 4: Build a reviewer packet
Review @architecture-decision-records using the copied upstream files plus provenance, then summarize any gaps before merge.
Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.
Best Practices
Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.
- Write ADRs early - Before implementation starts
- Keep them short - 1-2 pages maximum
- Be honest about trade-offs - Include real cons
- Link related decisions - Build decision graph
- Update status - Deprecate when superseded
- Don't change accepted ADRs - Write new ones to supersede
- Don't skip context - Future readers need background
Imported Operating Notes
Imported: Best Practices
Do's
- Write ADRs early - Before implementation starts
- Keep them short - 1-2 pages maximum
- Be honest about trade-offs - Include real cons
- Link related decisions - Build decision graph
- Update status - Deprecate when superseded
Don'ts
- Don't change accepted ADRs - Write new ones to supersede
- Don't skip context - Future readers need background
- Don't hide failures - Rejected decisions are valuable
- Don't be vague - Specific decisions, specific consequences
- Don't forget implementation - ADR without action is waste
Troubleshooting
Problem: The operator skipped the imported context and answered too generically
Symptoms: The result ignores the upstream workflow in
plugins/antigravity-awesome-skills-claude/skills/architecture-decision-records, fails to mention provenance, or does not use any copied source files at all.
Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Load only the files that materially change the answer, then restate the provenance before continuing.
Problem: The imported workflow feels incomplete during review
Symptoms: Reviewers can see the generated
SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task.
Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.
Problem: The task drifted into a different specialization
Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.
Related Skills
- Use when the work is better handled by that native specialization after this imported skill establishes context.@00-andruia-consultant
- Use when the work is better handled by that native specialization after this imported skill establishes context.@10-andruia-skill-smith
- Use when the work is better handled by that native specialization after this imported skill establishes context.@20-andruia-niche-intelligence
- Use when the work is better handled by that native specialization after this imported skill establishes context.@3d-web-experience
Additional Resources
Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.
| Resource family | What it gives the reviewer | Example path |
|---|---|---|
| copied reference notes, guides, or background material from upstream | |
| worked examples or reusable prompts copied from upstream | |
| upstream helper scripts that change execution or validation | |
| routing or delegation notes that are genuinely part of the imported package | |
| supporting assets or schemas copied from the source package | |
Imported Reference Notes
Imported: References
- PostgreSQL JSON Documentation
- PostgreSQL Full Text Search
- Internal: Performance benchmarks in
/docs/benchmarks/database-comparison.md
### Template 2: Lightweight ADR ```markdown # ADR-0012: Adopt TypeScript for Frontend Development **Status**: Accepted **Date**: 2024-01-15 **Deciders**: @alice, @bob, @charlie #### Imported: References - [Event Sourcing by Martin Fowler](https://martinfowler.com/eaaDev/EventSourcing.html) - [EventStoreDB Documentation](https://www.eventstore.com/docs)
Imported: Index
| ADR | Title | Status | Date |
|---|---|---|---|
| 0001 | Use PostgreSQL as Primary Database | Accepted | 2024-01-10 |
| 0002 | Caching Strategy with Redis | Accepted | 2024-01-12 |
| 0003 | MongoDB for User Profiles | Deprecated | 2023-06-15 |
| 0020 | Deprecate MongoDB | Accepted | 2024-01-15 |
Imported: Resources
Imported: Templates
Template 1: Standard ADR (MADR Format)
# ADR-0001: Use PostgreSQL as Primary Database #### Imported: Status Accepted #### Imported: Context We need to select a primary database for our new e-commerce platform. The system will handle: - ~10,000 concurrent users - Complex product catalog with hierarchical categories - Transaction processing for orders and payments - Full-text search for products - Geospatial queries for store locator The team has experience with MySQL, PostgreSQL, and MongoDB. We need ACID compliance for financial transactions. #### Imported: Decision Drivers * **Must have ACID compliance** for payment processing * **Must support complex queries** for reporting * **Should support full-text search** to reduce infrastructure complexity * **Should have good JSON support** for flexible product attributes * **Team familiarity** reduces onboarding time #### Imported: Considered Options ### Option 1: PostgreSQL - **Pros**: ACID compliant, excellent JSON support (JSONB), built-in full-text search, PostGIS for geospatial, team has experience - **Cons**: Slightly more complex replication setup than MySQL ### Option 2: MySQL - **Pros**: Very familiar to team, simple replication, large community - **Cons**: Weaker JSON support, no built-in full-text search (need Elasticsearch), no geospatial without extensions ### Option 3: MongoDB - **Pros**: Flexible schema, native JSON, horizontal scaling - **Cons**: No ACID for multi-document transactions (at decision time), team has limited experience, requires schema design discipline #### Imported: Decision We will use **PostgreSQL 15** as our primary database. #### Imported: Rationale PostgreSQL provides the best balance of: 1. **ACID compliance** essential for e-commerce transactions 2. **Built-in capabilities** (full-text search, JSONB, PostGIS) reduce infrastructure complexity 3. **Team familiarity** with SQL databases reduces learning curve 4. **Mature ecosystem** with excellent tooling and community support The slight complexity in replication is outweighed by the reduction in additional services (no separate Elasticsearch needed). #### Imported: Consequences ### Positive - Single database handles transactions, search, and geospatial queries - Reduced operational complexity (fewer services to manage) - Strong consistency guarantees for financial data - Team can leverage existing SQL expertise ### Negative - Need to learn PostgreSQL-specific features (JSONB, full-text search syntax) - Vertical scaling limits may require read replicas sooner - Some team members need PostgreSQL-specific training ### Risks - Full-text search may not scale as well as dedicated search engines - Mitigation: Design for potential Elasticsearch addition if needed #### Imported: Implementation Notes - Use JSONB for flexible product attributes - Implement connection pooling with PgBouncer - Set up streaming replication for read replicas - Use pg_trgm extension for fuzzy search #### Imported: Context Our React codebase has grown to 50+ components with increasing bug reports related to prop type mismatches and undefined errors. PropTypes provide runtime-only checking. #### Imported: Decision Adopt TypeScript for all new frontend code. Migrate existing code incrementally. #### Imported: Consequences **Good**: Catch type errors at compile time, better IDE support, self-documenting code. **Bad**: Learning curve for team, initial slowdown, build complexity increase. **Mitigations**: TypeScript training sessions, allow gradual adoption with `allowJs: true`.
Template 3: Y-Statement Format
# ADR-0015: API Gateway Selection In the context of **building a microservices architecture**, facing **the need for centralized API management, authentication, and rate limiting**, we decided for **Kong Gateway** and against **AWS API Gateway and custom Nginx solution**, to achieve **vendor independence, plugin extensibility, and team familiarity with Lua**, accepting that **we need to manage Kong infrastructure ourselves**.
Template 4: ADR for Deprecation
# ADR-0020: Deprecate MongoDB in Favor of PostgreSQL #### Imported: Status Accepted (Supersedes ADR-0003) #### Imported: Context ADR-0003 (2021) chose MongoDB for user profile storage due to schema flexibility needs. Since then: - MongoDB's multi-document transactions remain problematic for our use case - Our schema has stabilized and rarely changes - We now have PostgreSQL expertise from other services - Maintaining two databases increases operational burden #### Imported: Decision Deprecate MongoDB and migrate user profiles to PostgreSQL. #### Imported: Migration Plan 1. **Phase 1** (Week 1-2): Create PostgreSQL schema, dual-write enabled 2. **Phase 2** (Week 3-4): Backfill historical data, validate consistency 3. **Phase 3** (Week 5): Switch reads to PostgreSQL, monitor 4. **Phase 4** (Week 6): Remove MongoDB writes, decommission #### Imported: Consequences ### Positive - Single database technology reduces operational complexity - ACID transactions for user data - Team can focus PostgreSQL expertise ### Negative - Migration effort (~4 weeks) - Risk of data issues during migration - Lose some schema flexibility #### Imported: Lessons Learned Document from ADR-0003 experience: - Schema flexibility benefits were overestimated - Operational cost of multiple databases was underestimated - Consider long-term maintenance in technology decisions
Template 5: Request for Comments (RFC) Style
# RFC-0025: Adopt Event Sourcing for Order Management #### Imported: Motivation Current challenges: 1. Audit requirements need complete order history 2. "What was the order state at time X?" queries are impossible 3. Analytics team needs event stream for real-time dashboards 4. Order state reconstruction for customer support is manual #### Imported: Detailed Design ### Event Store
OrderCreated { orderId, customerId, items[], timestamp } OrderItemAdded { orderId, item, timestamp } OrderItemRemoved { orderId, itemId, timestamp } PaymentReceived { orderId, amount, paymentId, timestamp } OrderShipped { orderId, trackingNumber, timestamp }
### Projections - **CurrentOrderState**: Materialized view for queries - **OrderHistory**: Complete timeline for audit - **DailyOrderMetrics**: Analytics aggregation ### Technology - Event Store: EventStoreDB (purpose-built, handles projections) - Alternative considered: Kafka + custom projection service #### Imported: Drawbacks - Learning curve for team - Increased complexity vs. CRUD - Need to design events carefully (immutable once stored) - Storage growth (events never deleted) #### Imported: Alternatives 1. **Audit tables**: Simpler but doesn't enable temporal queries 2. **CDC from existing DB**: Complex, doesn't change data model 3. **Hybrid**: Event source only for order state changes #### Imported: Unresolved Questions - [ ] Event schema versioning strategy - [ ] Retention policy for events - [ ] Snapshot frequency for performance #### Imported: Implementation Plan 1. Prototype with single order type (2 weeks) 2. Team training on event sourcing (1 week) 3. Full implementation and migration (4 weeks) 4. Monitoring and optimization (ongoing) #### Imported: ADR Management ### Directory Structure
docs/ ├── adr/ │ ├── README.md # Index and guidelines │ ├── template.md # Team's ADR template │ ├── 0001-use-postgresql.md │ ├── 0002-caching-strategy.md │ ├── 0003-mongodb-user-profiles.md # [DEPRECATED] │ └── 0020-deprecate-mongodb.md # Supersedes 0003
### ADR Index (README.md) ```markdown # Architecture Decision Records This directory contains Architecture Decision Records (ADRs) for [Project Name]. #### Imported: Creating a New ADR 1. Copy `template.md` to `NNNN-title-with-dashes.md` 2. Fill in the template 3. Submit PR for review 4. Update this index after approval #### Imported: ADR Status - **Proposed**: Under discussion - **Accepted**: Decision made, implementing - **Deprecated**: No longer relevant - **Superseded**: Replaced by another ADR - **Rejected**: Considered but not adopted
Automation (adr-tools)
# Install adr-tools brew install adr-tools # Initialize ADR directory adr init docs/adr # Create new ADR adr new "Use PostgreSQL as Primary Database" # Supersede an ADR adr new -s 3 "Deprecate MongoDB in Favor of PostgreSQL" # Generate table of contents adr generate toc > docs/adr/README.md # Link related ADRs adr link 2 "Complements" 1 "Is complemented by"
Imported: ADR Review Checklist
Before Submission
- Context clearly explains the problem
- All viable options considered
- Pros/cons balanced and honest
- Consequences (positive and negative) documented
- Related ADRs linked
During Review
- At least 2 senior engineers reviewed
- Affected teams consulted
- Security implications considered
- Cost implications documented
- Reversibility assessed
After Acceptance
- ADR index updated
- Team notified
- Implementation tickets created
- Related documentation updated
#### Imported: Limitations - Use this skill only when the task clearly matches the scope described above. - Do not treat the output as a substitute for environment-specific validation, testing, or expert review. - Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.