ADR Decision Extraction

Extract architectural decisions from conversation context for ADR generation.

Detection Signals

Signal Type	Examples
Explicit markers	INLINECODE0, "decided:", "the decision is"
Choice patterns

"let's go with X", "we'll use Y", "choosing Z" | | Trade-off discussions | "X vs Y", "pros/cons", "considering alternatives" | | Problem-solution pairs | "the problem is... so we'll..." |

Extraction Rules

Explicit Tags (Guaranteed Inclusion)

Text marked with [ADR] is always extracted:

CODEBLOCK0

These receive confidence: "high" automatically.

AI-Detected Decisions

Patterns detected without explicit tags require confidence assessment:

Confidence	Criteria
high	Clear statement of choice with rationale
medium

Implied decision from action taken |
| low | Contextual inference, may need verification |

Output Format

CODEBLOCK1

Field Definitions

Field	Required	Description
INLINECODE3	Yes	Concise decision summary
INLINECODE4

Yes | Problem or context driving the decision | | chosen_option | Yes | The selected solution or approach | | alternatives_discussed | No | Other options mentioned (empty array if none) | | drivers | No | Factors influencing the decision | | confidence | Yes | high, medium, or low | | source_context | No | Brief description of where decision appeared |

Extraction Workflow

1. 1. Scan for explicit markers - Find all [ADR] tagged content
2. Identify choice patterns - Look for decision language
3. Extract trade-off discussions - Capture alternatives and reasoning
4. Assess confidence - Rate each non-explicit decision
5. Capture context - Note surrounding discussion for ADR writer

Pattern Examples

High Confidence

CODEBLOCK2

Extracts:

• - Title: Use Redis for caching
• Problem: Need fast caching with TTL
• Chosen: Redis
• Alternatives: Memcached
• Drivers: sub-millisecond latency, native TTL, persistence
• Confidence: high

Medium Confidence

CODEBLOCK3

Extracts:

• - Title: Use TypeScript for frontend
• Problem: Language choice for frontend
• Chosen: TypeScript
• Alternatives: (none stated)
• Drivers: consistency with backend
• Confidence: medium

Low Confidence

CODEBLOCK4

Extracts:

• - Title: REST API architecture
• Problem: API design approach
• Chosen: REST
• Alternatives: (none stated)
• Drivers: (none stated)
• Confidence: low

Best Practices

Context Capture

Always capture sufficient context for the ADR writer:

• - What was the discussion about?
• Who was involved (if known)?
• What prompted the decision?

Merge Related Decisions

If multiple statements relate to the same decision, consolidate them:

• - Combine alternatives from different mentions
• Aggregate drivers
• Use highest confidence level

Flag Ambiguity

When decisions are unclear or contradictory:

• - Note the ambiguity in INLINECODE14
• Set confidence to INLINECODE15
• Include all interpretations if multiple exist

When to Use This Skill

• - Analyzing session transcripts for ADR generation
• Reviewing conversation history for documentation
• Extracting decisions from design discussions
• Preparing input for ADR writing tools