context-save

Save a decision record, strategic bet, or learning to the persistent context registry.

Vision to Value Phase

Phase 6: Learning & Adaptation - This skill persists organizational knowledge for future use.

Prerequisites: Decision record, strategic bet, or learning created Outputs used by: All phases (enables organizational memory)

Auto-Initialization

Before saving, ensure the context folder structure exists. If any required folder or file is missing, create it:

1. Check if context/ folder exists - if not, inform user to run /setup first OR create the basic structure:

   • context/decisions/index.md
   • context/bets/index.md
   • context/assumptions/registry.md
   • context/portfolio/active-bets.md
   • context/learnings/index.md

2. When creating year folders (context/decisions/2026/), create them automatically.

Purpose

The context registry provides organizational memory. This skill extracts key information from documents and saves them to the appropriate index, enabling future recall and cross-referencing.

When to Use

Invoke /context-save after:

• Creating a decision record with /decision-record
• Formulating a strategic bet with /strategic-bet
• Completing a retrospective with /retrospective
• Completing an outcome review with /outcome-review
• Completing a decision quality audit with /decision-quality-audit

Process

1. Identify What to Save

Ask the user what they want to save:

• Decision Record → Extract to context/decisions/
• Strategic Bet → Extract to context/bets/ and context/portfolio/
• Learning → Extract to context/learnings/
• Assumptions → Extract to context/assumptions/registry.md

2. Extract Key Information

For Decision Records

Extract and save:

| ID | Title | Date | Owner | Product | Status | Tags |

• Include Product field if specified (for multi-product organizations)
• Generate tags from content (3-5 relevant keywords)
• Link related decisions if mentioned
• Extract assumptions to assumption registry

For Strategic Bets

Extract and save:

| ID | Title | Date | Owner | Product | Status | Key Assumption |

• Include Product field if specified (for multi-product organizations)
• Add to context/portfolio/active-bets.md if status is Active
• Extract ALL explicit assumptions to context/assumptions/registry.md
• Note upcoming checkpoints

For Learnings

Extract and save:

| ID | Learning | Source | Date | Product | Tags | Confidence |

• Include Product field if applicable (for multi-product organizations)
• Categorize by type (Strategy, Product, GTM, Customer, Process)
• Link to source document

For Assumptions

Extract and save:

| ID | Assumption | Source | Confidence | Validation Method | Status | Outcome |

• Generate assumption ID (A-NNN, sequential)
• Link back to source decision/bet
• Set initial status to "Pending"

3. Update Index Files

1. Read the current index file
2. Add the new entry to the appropriate table
3. Update "Last updated" timestamp
4. Update quick filters/categories
5. Write the updated index

4. Save Full Record

For decisions and bets, also save the full record:

• Create year folder if needed: context/[type]/[YYYY]/
• Save full document as [ID].md

5. Update JSON Index

Also update context/index.json for fast retrieval:

1. Read context/index.json
2. Add entry to the entries array:

   {
     "id": "DR-2026-001",
     "title": "API Versioning Strategy",
     "type": "decision",
     "path": "context/decisions/2026/DR-2026-001.md",
     "topics": ["api", "versioning", "compatibility"],
     "phase": "phase2",
     "created": "2026-01-25",
     "lastAccessed": "2026-01-25"
   }
   

3. Update topicIndex - add ID to each topic array
4. Update typeIndex - add ID to the type array (decision, bet, learning)
5. Update phaseIndex - add ID to the appropriate phase array
6. Update lastUpdated timestamp
7. Write updated JSON

Topic extraction:

• Use tags from the document
• Extract key terms from title
• Include product name if multi-product org

6. Confirm Save

Report what was saved:

Saved to context registry:
- Decision DR-2026-001 added to decisions/index.md
- 3 assumptions extracted to assumptions/registry.md
- Full record saved to decisions/2026/DR-2026-001.md
- JSON index updated (topics: api, versioning, compatibility)

Instructions

1. Ask what type of content to save (or detect from recent conversation)
2. If the content was just created, extract from it directly
3. If content is in a file, read it using @path/to/file.md syntax
4. Extract metadata following the formats above
5. Read current index files before updating
6. Preserve existing entries when adding new ones
7. Generate sequential IDs based on existing entries
8. Update all affected index files
9. Report what was saved and where

ID Generation

• Decisions: DR-[YYYY]-[NNN] (e.g., DR-2026-001)
• Bets: SB-[YYYY]-[NNN] (e.g., SB-2026-003)
• Assumptions: A-[NNN] (e.g., A-015) - sequential across all assumptions
• Learnings: L-[NNN] (e.g., L-042) - sequential across all learnings

Check existing indexes to determine next available number.

Cross-Reference Extraction (v3)

After saving a new entry to the context registry:

1. Scan for ID references: Look for patterns matching existing IDs (DR-, SB-, FB-, A-, L-, DOC-) in the entry content
2. Create bidirectional links: Update crossReferences in context/index.json
3. Update topic indexes: Add entry keywords to topicIndex, productIndex, and phaseIndex as appropriate
4. Log what was linked: Include cross-reference summary in the save confirmation

See rules/context-graph.md for the full cross-reference specification.