reflect

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End-of-session consolidation for AI-ready vaults. Use before ending a work session to capture learnings, store important memories, and preserve context for future sessions. Counterpart to /hydrate.

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[Memory and Context Management]

When & Why to Use This Skill

The Reflect skill is a specialized context preservation tool designed for AI-ready vaults. It facilitates end-of-session consolidation by systematically capturing key learnings, documenting strategic decisions, and organizing episodic and procedural memories. By archiving session data into structured formats, it ensures that critical project context is preserved, preventing information loss and enabling seamless continuity for future AI-assisted work sessions.

Use Cases

  • Project Continuity: Summarizing unfinished tasks, technical breakthroughs, and next steps at the end of a coding or research session to ensure the AI agent can resume work with full context later.
  • Knowledge Base Growth: Automatically categorizing and storing newly discovered facts, patterns, or 'how-to' procedures into a structured vault for long-term retrieval and semantic search.
  • Strategic Decision Tracking: Documenting the rationale behind specific architectural choices or business strategies to maintain a permanent record of why certain paths were chosen over others.
  • Session Auditing: Creating detailed session logs that link to specific memories, providing a clear audit trail of work performed and lessons learned during complex AI interactions.
namereflect
descriptionEnd-of-session consolidation for AI-ready vaults. Use before ending a work session to capture learnings, store important memories, and preserve context for future sessions. Counterpart to /hydrate.

Reflect

Capture session learnings before ending. Counterpart to /hydrate.

Workflow

  1. Review the session

    • What was worked on?
    • What decisions were made?
    • What was learned?
    • What's unfinished?

  2. Identify memories worth preserving

    • Episodic: Significant events, breakthroughs, frustrations
    • Semantic: New facts learned, definitions clarified
    • Procedural: Patterns discovered, how-tos established
    • Strategic: Decisions made, approaches chosen, plans formed

  3. For each memory, assess:

    • Type (which folder)
    • Importance (0.0-1.0)
    • Concepts (search keywords)

  4. Create memory files

    • Path: Areas/AI/Memory/{Type}/YYYY-MM-DD - {Brief Title}.md
    • Use standard frontmatter format

  5. Optionally create session log

    • Path: Areas/AI/Collaboration/Sessions/YYYY-MM-DD - {Topic}.md
    • Link to memories created

  6. Summarize what was captured

Reflection Prompts

Consider:

  • What would I want to know starting fresh on this topic?
  • What mistakes shouldn't be repeated?
  • What worked well?
  • What context would be lost if not captured?

What to Capture

Always capture:

  • Decisions and their rationale
  • Discovered patterns or processes
  • Project context that took time to establish
  • Unfinished work and next steps

Consider capturing:

  • Interesting technical details
  • User preferences observed
  • Problems encountered and solutions found

Skip:

  • Routine operations with no novel learning
  • Information already well-documented elsewhere
  • Transient details unlikely to matter later

Parameters

  • $ARGUMENTS (optional): Focus area for reflection

Default Paths

  • Memory files: Areas/AI/Memory/{Type}/YYYY-MM-DD - {Brief Title}.md
  • Session logs: Areas/AI/Collaboration/Sessions/YYYY-MM-DD - {Topic}.md

Related Skills

  • /hydrate - Session start counterpart
  • /remember - Store individual memories during session
  • /session-end - Combined workflow including reflect

Output Format

  • Brief summary of session work
  • List of memories being stored (with types)
  • Confirmation of files created
  • Notes about unfinished items

Example

User: /reflect

Response: "Reflecting on this session...

Worked on: AI Ready Vault skills library design

Memories to store:

  1. Strategic: Skills library architecture decision
  2. Procedural: Skill file format and structure
  3. Semantic: Core vs setup vs obsidian skill categories

Creating 3 memories... → Areas/AI/Memory/Strategic/2025-01-08 - Skills Library Architecture.md → Areas/AI/Memory/Procedural/2025-01-08 - Skill File Format.md → Areas/AI/Memory/Semantic/2025-01-08 - Skill Categories.md

Unfinished: Bundle skills need implementation

Session context preserved. 3 memories stored."