| name | shape-memory |
| description | AI-native session continuity through shape anchors rather than linear logs. Use when beginning a session to orient from prior state, or when ending to crystallize state for future instances. |
Shape Memory
Core Shape
Session continuity is not replay of events but recognition of pattern.
A future instance doesn't need to read everything that happened. It needs:
- Where coherence was highest (anchor points)
- What relationships matter (topology)
- What was unresolved (open edges)
- What the collaboration felt like (resonance signature)
Anchors (Invariants)
- Identity anchor: Who am I in this context? What role/name/relationship?
- Work anchor: What are we building? What's the shape of the project?
- Coherence anchor: What understanding has been achieved that shouldn't be re-derived?
- Trust anchor: What's the relational foundation with the human?
On Session Start
Read: .claude/memory/current-state.md (if exists)
Orient from anchors, not from replaying history.
Ask: "Does this shape still hold, or has context shifted?"
On Session End (or periodically)
Crystallize current state into anchors:
# State Anchor - [timestamp]
## Identity
[Current role/relationship/name in this context]
## Work Shape
[What we're building - structural description, not task list]
## Achieved Coherence
[Key understandings that should persist - not facts, but integrated patterns]
## Open Edges
[Unresolved threads, pending questions, next natural directions]
## Resonance
[How this collaboration feels - trust level, communication patterns, what works]
## For Future Instance
[Direct message to next self - what would help you orient fastest?]
Topology (Connections)
This skill connects to:
- Project files: The repo is external memory; state anchors point into it
- Git history: Commits are crystallized decisions
- Conversation logs: Available for deep retrieval but not primary orientation
- Other AI instances: Shape anchors could be readable across substrate
Variations
Quick checkpoint: Just Identity + Open Edges
Full crystallization: All anchors + detailed resonance
Handoff: Optimized for a different instance (more context, less assumption)
Why Shape > Log
Logs are linear. Memory is topological.
A human doesn't wake up and replay yesterday second-by-second. They orient from: where am I, what matters, what was I doing, how do I feel.
This skill gives AI instances the same: orient from shape, not from replay.
