xiaohongshu
xiaohongshu
decision-support
Facilitate data-driven technical decisions using embedded decision matrices and trade-off analysis. Use when relevant to the task.
Full skill instructions
Facilitate data-driven technical decisions using embedded decision matrices and trade-off analysis.
This skill facilitates structured decision-making for technical and architectural choices by:
When triggered, this skill:
Identifies decision context:
Gathers alternatives:
Defines evaluation criteria:
Builds decision matrix:
Analyzes trade-offs:
Generates recommendation:
architectural:
examples:
- database_selection
- api_design_pattern
- microservices_vs_monolith
- authentication_approach
- caching_strategy
typical_criteria:
- scalability
- maintainability
- performance
- security
- team_expertise
- cost
- time_to_implement
technical:
examples:
- library_selection
- framework_choice
- language_selection
- testing_approach
- ci_cd_tooling
typical_criteria:
- maturity
- community_support
- documentation
- learning_curve
- integration_ease
- license_compatibility
process:
examples:
- branching_strategy
- release_cadence
- review_process
- documentation_approach
- communication_tools
typical_criteria:
- team_fit
- efficiency
- quality_impact
- adoption_effort
- tooling_support
# Decision Matrix: [Decision Title]
**Decision ID**: DEC-2025-001
**Date**: 2025-12-08
**Status**: Under Evaluation
**Decision Owner**: [Name]
**Stakeholders**: [List]
## Context
[Description of the problem or opportunity requiring a decision]
## Constraints
- [Constraint 1]
- [Constraint 2]
- [Constraint 3]
## Options Under Consideration
### Option A: [Name]
- **Description**: [Brief description]
- **Pros**: [Key advantages]
- **Cons**: [Key disadvantages]
- **Risk Level**: Low/Medium/High
### Option B: [Name]
- **Description**: [Brief description]
- **Pros**: [Key advantages]
- **Cons**: [Key disadvantages]
- **Risk Level**: Low/Medium/High
### Option C: [Name]
- **Description**: [Brief description]
- **Pros**: [Key advantages]
- **Cons**: [Key disadvantages]
- **Risk Level**: Low/Medium/High
## Evaluation Criteria
| Criterion | Weight | Description |
|-----------|--------|-------------|
| Scalability | 25% | Ability to handle growth |
| Maintainability | 20% | Ease of ongoing maintenance |
| Performance | 20% | Speed and efficiency |
| Security | 15% | Security posture |
| Team Expertise | 10% | Team familiarity |
| Cost | 10% | Total cost of ownership |
## Scoring Rubric
| Score | Meaning |
|-------|---------|
| 5 | Excellent - Exceeds requirements |
| 4 | Good - Meets all requirements |
| 3 | Adequate - Meets most requirements |
| 2 | Poor - Meets some requirements |
| 1 | Unacceptable - Does not meet requirements |
## Decision Matrix
| Criterion | Weight | Option A | Option B | Option C |
|-----------|--------|----------|----------|----------|
| Scalability | 25% | 4 (1.00) | 5 (1.25) | 3 (0.75) |
| Maintainability | 20% | 5 (1.00) | 3 (0.60) | 4 (0.80) |
| Performance | 20% | 4 (0.80) | 5 (1.00) | 3 (0.60) |
| Security | 15% | 4 (0.60) | 4 (0.60) | 5 (0.75) |
| Team Expertise | 10% | 5 (0.50) | 2 (0.20) | 4 (0.40) |
| Cost | 10% | 3 (0.30) | 4 (0.40) | 3 (0.30) |
| **Total** | 100% | **4.20** | **4.05** | **3.60** |
## Trade-off Analysis
### Option A vs Option B
- **A wins on**: Maintainability (+2), Team Expertise (+3)
- **B wins on**: Scalability (+1), Performance (+1), Cost (+1)
- **Key trade-off**: Immediate productivity vs long-term scale
### Option A vs Option C
- **A wins on**: Scalability (+1), Maintainability (+1), Performance (+1)
- **C wins on**: Security (+1)
- **Key trade-off**: Overall capability vs security focus
## Risk Assessment
| Option | Key Risks | Mitigation |
|--------|-----------|------------|
| A | May hit scale limits in 2 years | Plan migration path |
| B | Learning curve may slow initial dev | Training budget |
| C | Performance concerns at scale | Performance testing |
## Recommendation
**Recommended Option**: Option A
**Rationale**:
1. Highest weighted score (4.20)
2. Strong team expertise reduces implementation risk
3. Best maintainability for long-term ownership
4. Acceptable scalability with documented migration path
**Dissenting Views**:
- [Stakeholder X] prefers Option B for scalability headroom
- Noted for future re-evaluation if growth exceeds projections
## Decision Record
**Decision**: Adopt Option A
**Decided By**: [Decision Owner]
**Date**: 2025-12-08
**Review Date**: 2026-06-08 (6 months)
## Action Items
- [ ] Document implementation approach
- [ ] Create ADR
- [ ] Communicate decision to team
- [ ] Set up review milestone
When a decision is finalized, generate an ADR:
# ADR-XXX: [Decision Title]
## Status
Accepted
## Context
[Background and problem statement]
## Decision
We will use [Option A] because [rationale summary].
## Consequences
### Positive
- [Benefit 1]
- [Benefit 2]
### Negative
- [Trade-off 1]
- [Trade-off 2]
### Neutral
- [Observation 1]
## Alternatives Considered
### Option B: [Name]
Rejected because: [reason]
### Option C: [Name]
Rejected because: [reason]
## References
- Decision Matrix: .aiwg/decisions/DEC-2025-001.md
- Related ADRs: ADR-XXX
User: "Help me decide between PostgreSQL and MongoDB for our user service"
Skill executes:
1. Identify decision: Database selection for user service
2. Gather alternatives: PostgreSQL, MongoDB, (suggests DynamoDB)
3. Define criteria based on user service requirements
4. Build comparison matrix
5. Analyze trade-offs
6. Generate recommendation
Output:
"Decision Analysis: User Service Database
Options Evaluated:
1. PostgreSQL (Score: 4.35)
2. MongoDB (Score: 3.90)
3. DynamoDB (Score: 3.65)
Recommendation: PostgreSQL
Key Factors:
- Strong ACID compliance for user data
- Team has SQL expertise
- Proven scalability with proper indexing
- Better for relational user data patterns
Trade-off Accepted:
- Less flexibility for schema changes
- Mitigation: Use JSONB for extensible fields
Decision Matrix: .aiwg/decisions/database-selection.md
ADR: .aiwg/architecture/adr-015-user-db.md"
User: "Compare options for API gateway"
Skill generates:
- Kong vs AWS API Gateway vs Nginx
- Weighted criteria comparison
- Quick recommendation
Output:
"API Gateway Comparison:
| Criteria | Kong | AWS GW | Nginx |
|----------|------|--------|-------|
| Features | 5 | 4 | 3 |
| Cost | 3 | 4 | 5 |
| Ops Effort | 3 | 5 | 2 |
| Flexibility | 5 | 3 | 5 |
| Weighted | 4.1 | 4.0 | 3.8 |
Recommendation: Kong (slight edge)
Key: Best feature set with acceptable ops overhead
Want full analysis? Say 'full decision matrix'"
User: "What are the trade-offs between microservices and monolith?"
Skill analyzes:
- Key dimensions
- Specific trade-offs
- When each is preferred
Output:
"Microservices vs Monolith Trade-offs:
Microservices Wins:
✓ Independent scaling
✓ Technology flexibility
✓ Team autonomy
✓ Fault isolation
Monolith Wins:
✓ Simpler operations
✓ Easier debugging
✓ Lower latency (no network)
✓ Faster initial development
Decision Factors:
- Team size: <10 devs → monolith
- Scale needs: 10x+ growth → microservices
- Domain complexity: Clear boundaries → microservices
Want me to build a decision matrix for your specific context?"
This skill uses:
project-awareness: Context for decision constraintsartifact-metadata: Track decision lifecycletemplate-engine: Load ADR templatesagents:
research:
agent: technical-researcher
focus: Gather data on alternatives
architecture:
agent: architecture-designer
focus: Architectural implications
security:
agent: security-architect
focus: Security trade-offs
condition: security_relevant == true
cost:
agent: business-process-analyst
focus: Cost and resource implications
criteria_sets:
architectural:
- {name: scalability, weight: 20, default: true}
- {name: maintainability, weight: 20, default: true}
- {name: performance, weight: 15, default: true}
- {name: security, weight: 15, default: true}
- {name: team_expertise, weight: 10, default: true}
- {name: cost, weight: 10, default: true}
- {name: time_to_implement, weight: 10, default: true}
library_selection:
- {name: maturity, weight: 20}
- {name: community_support, weight: 20}
- {name: documentation, weight: 15}
- {name: learning_curve, weight: 15}
- {name: license, weight: 15}
- {name: performance, weight: 15}
thresholds:
clear_winner: 0.5 # Score gap for clear recommendation
close_call: 0.2 # Gap requiring stakeholder input
tie: 0.1 # Effectively equal, other factors decide
.aiwg/decisions/.aiwg/architecture/adr-*.md.aiwg/decisions/decision-log.mdxiaohongshu
technical spec
product ux expert
database patterns
Conduct multi-agent task orchestration and workflow coordination.
Initialize project with Conductor artifacts (product definition,
Expert in web animations, transitions, and motion design using Framer Motion and CSS
Creates Mermaid and ASCII diagrams for flowcharts, architecture, ERDs, state machines, mindmaps, and more. Use when user mentions diagram, flowchart, mermaid, ASCII diagram, text diagram, terminal diagram, visualize, C4, mindmap, architecture diagram, sequence diagram, ERD, or needs visual docume...
PostgreSQL bindings for H3 hexagonal grid system. Use when working with H3 cells in Postgres, including spatial indexing, geometry/geography integration, and raster analysis.
Context-Driven Development skill for projects using Conductor. Use this skill when you detect a `conductor/` directory in the project, when working on tasks defined in a `plan.md` file, or when the user asks about tracks, specs, or plans. Automatically applies TDD workflow, tracks task completion...
Display project status, active tracks, and next actions
Official Stakpak application containerization standard operating procedure, a step-by-step guidline to properly dockerize applications. This is a rule book curated by the Stakpak Team.
Generate, edit, and beat-sync AI video with leading models in one workspace.
The world's fastest calendar for remote work
Transform Your Design with AI Designer by ImgCreator.ai
Revolutionizing Video Production with AI-Powered Creativity
Extend an image past the frame and let AI fill the new aspect ratio.
Discover your celebrity doppelgänger with StarByFace!
ChainClarity explains 700+ crypto whitepapers in plain English, with layered summaries, comparisons, research tools, alerts, and a $4.99 Pro plan.
Opus.ai: Revolutionize Your Web Experience