- name
- inner-life-evolve
- version
- 1.0.4
- homepage
- https://github.com/DKistenev/openclaw-inner-life
- source
- https://github.com/DKistenev/openclaw-inner-life/tree/main/skills/inner-life-evolve
- description
- 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.
- metadata
- clawdbot
- requires
- bins
- ["jq"]
- reads
- ["memory/", "BRAIN.md", "SELF.md"]
- writes
- ["tasks/QUEUE.md"]
- agent-discovery
- triggers
- bundle
- openclaw-inner-life
- works-with
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:
- Check that
memory/inner-state.jsonexists - Check that
BRAIN.mdexists - Check that
tasks/QUEUE.mdexists
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 patternsmemory/drive.json— seeking, avoidancememory/relationship.json— trust, lessonsmemory/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
Rationale: 1-2 sentences explaining why
Steps: concrete implementation stepsStep 4: Announce
Send summary to user: <= 5 sentences covering:
- Habits: [strong habits, new patterns]
- Trust changes: [trust dynamics]
- Recurring frustrations: [repeated problems → suggested fix]
- Seeking themes: [active research → suggested development]
Safety Rules
- Never auto-execute proposals — user approves first
- Brain Loop reads QUEUE and shows
[EVOLVER]tasks at lower priority - Tasks in Ready > 7 days without action → Brain Loop sends reminder
- Proposals should be specific and actionable, not vague "improve X"
Recommended Schedule
Run 1-2 times per week (e.g., Wednesday and Sunday evenings). Needs enough data to analyze — running daily produces low-quality proposals.
State Integration
Reads: everything (Context Level 4 Deep)
Writes: tasks/QUEUE.md only. Does NOT write to state files directly.
The evolver observes but doesn't touch the controls. It proposes. The user decides.
When Should You Install This?
Install this skill if:
- Your agent has plateaued and isn't improving
- You want structured self-improvement proposals
- You value evolution with human oversight
- You want your agent to challenge its own assumptions
Part of the openclaw-inner-life bundle. Requires: inner-life-core