Skill: dkistenev/inner-life-evolve (version 1.0.4)

--- 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: 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 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](https://github.com/DKistenev/openclaw-inner-life) bundle. Requires: inner-life-core


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)