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inner-life-memory

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.

dkistenev0 source installs☆ 0 Repository starsv1.0.4

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install dkistenev/inner-life-memory

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill instructions

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 | Mea...

Source information

Source
github
Repository
openclaw/skills
Path
skills/dkistenev/inner-life-memory
Version
1.0.4
Commit
26660e9fa68f07362ce8a0ad98765fdddd1e1e60
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

SKILL.md
# 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 | Mea...

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