Imported skill decision_capture from openai
Scanned 9/11/2026
Install to Claude Code
npx -y skills add bitwikiorg/skills.md --skill decision_capture --agent claude-codeInstalls into .claude/skills of the current project.
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---
description: Imported skill decision_capture from openai
name: decision_capture
signature: c6fc42d095d842ac55ab1a95322bab7d0146669089e0b0d470f791ad8477b586
source: /a0/tmp/skills_research/openai/skills/.curated/notion-knowledge-capture/examples/decision-capture.md
---
# Example: Decision Record Capture
**User Request**: "Document our decision to move from REST to GraphQL API"
## Workflow
### 1. Extract Decision from Context
From conversation, identified:
- **Decision**: Migrate customer-facing API from REST to GraphQL
- **Context**: REST endpoints becoming unwieldy (50+ endpoints)
- **Alternatives**: Keep REST, try gRPC, adopt GraphQL
- **Rationale**: Better client experience, type safety, single endpoint
### 2. Find Decision Log
```
Notion:notion-search
query: "architecture decisions" or "ADR"
```
Found: "Architecture Decision Records" database
### 3. Fetch Schema
```
Notion:notion-fetch
```
Got properties: Decision (title), Date, Status, Domain, Impact, Deciders, Stakeholders
### 4. Create Decision Record
```
Notion:notion-create-pages
parent: { data_source_id: "decision-log-collection-id" }
pages: [{
properties: {
"Decision": "Migrate to GraphQL API",
"date:Date:start": "2025-10-16",
"date:Date:is_datetime": 0,
"Status": "Accepted",
"Domain": "Architecture",
"Impact": "High"
},
content: "[Full decision record with context, rationale, alternatives...]"
}]
```
**Content sample**:
```markdown
# Migrate Customer-Facing API to GraphQL
## Context
Our REST API has grown to 50+ endpoints with inconsistent patterns. Frontend and mobile teams request new endpoints frequently, leading to:
- API bloat and maintenance burden
- Over-fetching/under-fetching data
- Slow iteration on client features
- Inconsistent error handling
## Decision
Migrate customer-facing API from REST to GraphQL while maintaining REST for internal services.
## Rationale
**Why GraphQL**:
- Clients fetch exactly what they need (no over/under-fetching)
- Single endpoint, self-documenting schema
- Type safety with code generation
- Better developer experience
- Industry standard for client-facing APIs
## Options Considered
### Option A: Keep REST (Status Quo)
**Pros**: No migration cost, team familiar
**Cons**: Doesn't solve core problems, maintenance keeps growing
**Decision**: Rejected - doesn't address root cause
### Option B: gRPC
**Pros**: Performance, strong typing
**Cons**: Browser support issues, steeper learning curve, not designed for client-facing
**Decision**: Rejected - better for internal services
### Option C: GraphQL
**Pros**: Solves over/under-fetching, great DX, strong ecosystem
**Cons**: Learning curve, caching complexity, migration effort
**Decision**: **Accepted**
## Consequences
**Positive**:
- Faster frontend/mobile development
- Reduced API maintenance burden
- Better type safety and tooling
- Single endpoint simplifies deployment
**Negative**:
- 3-4 month migration timeline
- Team needs training
- Need to solve caching strategy
- Monitoring/debugging patterns different
## Implementation Plan
1. GraphQL server setup (Apollo Server)
2. Schema design workshop
3. Gradual migration (start with new features)
4. Dual-run period (both REST and GraphQL)
5. Deprecate old REST endpoints
**Timeline**: Start Q4 2025, complete Q1 2026
**Owner**: Backend team lead
## Success Metrics
- API response times improve 30%
- Client fetch efficiency (less data transferred)
- Reduced new endpoint requests
- Developer satisfaction scores
```
### 5. Make Discoverable
Added link from Architecture Wiki and notified team in Slack.
## Key Success Factors
- Captured decision while context fresh
- Documented alternatives considered
- Included both pros and cons
- Clear implementation plan
- Saved to decision log for future reference
- Made discoverable for team
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