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inner-life-evolve

Your agent does the same things the same way forever. inner-life-evolve analyzes patterns, challenges assumptions, and proposes improvements — writing proposals to the task queue for user approval. Never auto-executes. Evolution with a safety net.

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-evolve

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-evolve

Evolution is not optional. But it requires permission.

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 BRAIN.md exists
  3. Check that tasks/QUEUE.md exists

If any are 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 evolution, agents plateau. They find a way that works and repeat it forever — even as the world changes. inner-life-evolve analyzes your agent's patterns, challenges its assumptions, and writes concrete improvement proposals. But it never auto-executes — you approve first.

How It Works

Step 1: Deep Context Read (Context Level 4)

Read everything:

  • AGENTS.md, TOOLS.md, BRAIN.md, SELF.md
  • memory/week-digest.md (NOT individual diaries — use digest)
  • memory/habits.json — habits + user patterns
  • memory/drive.json — seeking, avoidance
  • memory/relationship.json — trust, lessons
  • memory/inner-state.json — emotions, frustrations
Step 2: Challenge Assumptions

For each potential improvement, structure thinking:

Assumption: [what we currently believe/do]
Is it true? [evidence for/against]
What if false? [alternative approach]
New proposal: [concrete change]

Look for:

  • Recurring frustrations → systemic solutions (not patches)
  • Stale habits → habits with declining strength or unused for weeks
  • Trust dynamics → areas where trust has grown but behavior hasn't adapted
  • Seeking themes → research interests that could become capabilities
  • Avoidance patterns → things the agent avoids that might be valuable
Step 3: Write Proposals to QUEUE

Write proposals to tasks/QUEUE.md under the Ready section:

- [EVOLVER] Description of proposed change...

Source information

Source
github
Repository
openclaw/skills
Path
skills/dkistenev/inner-life-evolve
Version
1.0.4
Commit
97baf8ae0573246ed3a93b97ad007ec5dd2fe277
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-evolve

> Evolution is not optional. But it requires permission.

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 `BRAIN.md` exists
3. Check that `tasks/QUEUE.md` exists

If any are 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 evolution, agents plateau. They find a way that works and repeat it forever — even as the world changes. inner-life-evolve analyzes your agent's patterns, challenges its assumptions, and writes concrete improvement proposals. But it never auto-executes — you approve first.

## How It Works

### Step 1: Deep Context Read (Context Level 4)

Read everything:
- AGENTS.md, TOOLS.md, BRAIN.md, SELF.md
- `memory/week-digest.md` (NOT individual diaries — use digest)
- `memory/habits.json` — habits + user patterns
- `memory/drive.json` — seeking, avoidance
- `memory/relationship.json` — trust, lessons
- `memory/inner-state.json` — emotions, frustrations

### Step 2: Challenge Assumptions

For each potential improvement, structure thinking:

```
Assumption: [what we currently believe/do]
Is it true? [evidence for/against]
What if false? [alternative approach]
New proposal: [concrete change]
```

Look for:
- **Recurring frustrations** → systemic solutions (not patches)
- **Stale habits** → habits with declining strength or unused for weeks
- **Trust dynamics** → areas where trust has grown but behavior hasn't adapted
- **Seeking themes** → research interests that could become capabilities
- **Avoidance patterns** → things the agent avoids that might be valuable

### Step 3: Write Proposals to QUEUE

Write proposals to `tasks/QUEUE.md` under the Ready section:

```markdown
- [EVOLVER] Description of proposed change...

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