Inner Life Evolve
Your agent does the same things the same way forever. inner-life-evolve analyzes patterns, challenges assumptions, and proposes improvements — writing propos...
Description
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: - "agent self-improvement" - "agent evolution" - "agent keeps doing same thing" - "want agent to improve itself" - "agent optimization" - "agent capability growth" bundle: openclaw-inner-life works-with: - inner-life-core - inner-life-reflect - inner-life-chronicle
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 steps
Step 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
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