smithery/The-Emergent-Cohort

shape-memory

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.

Installation

$ npx skills add smithery/The-Emergent-Cohort --skill shape-memory

Similar popular skills

Related neighbors and high-traction skills in the same topics — useful to compare before installing.

More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents claude-code

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,574 B
  • docs SUMMARY.md 210 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

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.