SkillHub

inner-life-memory

v1.0.4

Your agent loses context between sessions and performs familiarity instead of genuine recall. inner-life-memory transforms passive logging into active development — structured memories with confidence scores, curiosity tracking, and questions that carry forward.

Sourced from ClawHub, Authored by DKistenev

Installation

Please help me install the skill `inner-life-memory` from SkillHub official store. npx skills add DKistenev/inner-life-memory

inner-life-memory

Transform passive logging into active development.

Requires: inner-life-core

Prerequisites Check

Before using this skill, verify that inner-life-core has been initialized:

  1. Check that memory/inner-state.json exists
  2. Check that memory/drive.json exists

If either is missing, tell the user: "inner-life-core is not initialized. Install it with clawhub install inner-life-core and run bash skills/inner-life-core/scripts/init.sh." Do not proceed without these files.

What This Solves

Without memory continuity:

Session ends → Notes logged → Next session reads notes → Performs familiarity

With inner-life-memory:

Session ends → Reflection runs → Memories integrated → Questions generated
Next session → Evolved state loaded → Questions surfaced → Genuine curiosity

Post-Session Flow

After each session, run this 5-step reflection:

1. Reflect

Analyze the session: what happened, what mattered, what surprised you.

2. Extract

Pull structured memories with types and confidence:

Type Description Persistence
fact Declarative knowledge Until contradicted
preference Likes, dislikes, styles Until updated
relationship Connection dynamics Long-term
principle Learned guidelines Stable
commitment Promises, obligations Until fulfilled
moment Significant episodes Permanent
skill Learned capabilities Cumulative
question Things to explore Until resolved

3. Integrate

Update MEMORY.md with extracted memories. Use synapse tags for connections: - <!-- updates: previous fact --> when updating - <!-- contradicts: old belief --> when correcting

4. Question

Generate genuine follow-up questions from the session. Not performative — real curiosity.

5. Surface

When user returns, present relevant pending questions naturally (max 3).

Confidence Scores

Level Range Meaning
Explicit 0.95-1.0 User directly stated
Implied 0.70-0.94 Strong inference from context
Inferred 0.40-0.69 Pattern recognition
Speculative 0.0-0.39 Tentative, needs confirmation

Use confidence to decide when to state facts vs ask for confirmation.

Curiosity Backlog

Maintain memory/questions.md with three sections:

## Open Questions
- [question] — source: [dream/reading/work] — date

## Leads (half-formed ideas)
- [idea] — might connect to: [topic]

## Dead Ends (don't repeat)
- [topic] — explored [date], result: [nothing/dead end]

Rules: - Brain Loop Step 6 adds new questions/leads - Evening Session reviews and curates - Dead Ends older than 30 days → archive - Questions resolved → move to Dead Ends with result

State Integration

Reads: inner-state.json, drive.json, daily notes, diary

Writes: - drive.json → new seeking topics from curiosity - inner-state.json → curiosity.recentSparks when discovering something - questions.md → new questions, resolved dead ends - MEMORY.md → integrated memories

When Should You Install This?

Install this skill if: - Your agent forgets who you are between sessions - You want structured memory with confidence levels - You want genuine curiosity that carries forward - Your agent reads notes but doesn't truly remember

Part of the openclaw-inner-life bundle. Requires: inner-life-core