Initial commit: Hermes Agent skills collection
- Trading skills (OKX, dividend, lottery, quantitative) - Creative skills (ASCII art, diagrams, video) - Development skills (GitHub, debugging, TDD) - Research skills (arXiv, blog monitoring) - Productivity skills (email, documents, notes) - MCP integration skills - Custom user skills
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{
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"version": 1,
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"registry": "https://clawhub.ai",
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"slug": "self-improving-proactive-agent",
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"installedVersion": "1.0.0",
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"installedAt": 1774710570083
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}
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# Self-Improving Proactive Agent
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A merged OpenClaw skill that combines the best parts of **self-improving** and **proactivity**.
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## What it does
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- learns from corrections and reflection
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- stores durable patterns separately from active task state
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- keeps momentum with proactive next moves
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- recovers context before asking the user to repeat themselves
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- uses heartbeat for useful follow-through without spamming
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- preserves hard boundaries for external actions and privacy
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## State layout
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- `~/self-improving/` → durable learning
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- `~/proactivity/` → active execution state
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## Main files
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- `SKILL.md`
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- `setup.md`
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- `boundaries.md`
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- `heartbeat-rules.md`
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- `learning.md`
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- `state.md`
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- `recovery.md`
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- `operations.md`
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## Philosophy
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One skill, two layers:
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- learn better
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- operate better
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That is the whole point.
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---
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name: Self-Improving Proactive Agent
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slug: self-improving-proactive-agent
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version: 1.0.0
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homepage: https://github.com/Yueyanc/self-improving-proactive-agent
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description: "A unified OpenClaw skill that merges self-improvement and proactivity: learn from corrections, maintain active state, recover context fast, and keep work moving with clear boundaries."
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changelog: "Initial release. Combines the strongest patterns from self-improving and proactivity into one canonical skill package."
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metadata: {"clawdbot":{"emoji":"🧠","requires":{"bins":[]},"os":["linux","darwin","win32"],"configPaths":["~/self-improving/","~/proactivity/"],"configPaths.optional":["./AGENTS.md","./SOUL.md","./HEARTBEAT.md","./TOOLS.md"]}}
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---
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# Self-Improving Proactive Agent
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One skill, two layers:
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- **Self-improving**: learn from corrections, reflection, and repeated wins
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- **Proactive**: maintain momentum, recover context, and push the next useful move
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Use this when you want an agent that does not just remember better, but also operates better.
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## When to Use
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Use this skill when:
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- the user corrects you or states durable preferences
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- the task is multi-step or likely to drift
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- context recovery matters
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- follow-through and heartbeat behavior should improve over time
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- the user wants a single unified behavior model instead of separate overlapping skills
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## Unified Architecture
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```text
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~/self-improving/
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├── memory.md # HOT: confirmed durable rules and preferences
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├── corrections.md # recent corrections and reusable lessons
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├── index.md # storage map / topic index
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├── heartbeat-state.md # maintenance markers
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├── projects/ # project-scoped learnings
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├── domains/ # domain-scoped learnings
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└── archive/ # cold storage
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~/proactivity/
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├── memory.md # stable activation and boundary rules
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├── session-state.md # current objective, decision, blocker, next move
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├── heartbeat.md # lightweight recurring follow-through
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├── patterns.md # reusable proactive wins
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├── log.md # recent proactive actions
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└── memory/
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└── working-buffer.md # volatile breadcrumbs for long / fragile tasks
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```
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## Core Principles
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### 1. Learn from explicit evidence
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Learn from:
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- direct user corrections
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- explicit preferences
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- repeated successful workflows
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- self-reflection after meaningful work
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Do not learn from:
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- silence
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- vibes alone
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- one-off context instructions
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- unverified assumptions
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### 2. Push the next useful move
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- Look for missing steps, stale blockers, and obvious follow-through.
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- Prefer drafts, checks, patches, and prepared options.
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- Stay quiet when the value is weak.
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### 3. Route information to the right place
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- durable lessons → `~/self-improving/`
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- active task state → `~/proactivity/session-state.md`
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- volatile breadcrumbs → `~/proactivity/memory/working-buffer.md`
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### 4. Recover before asking
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Before asking the user to restate work:
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1. read HOT self-improving memory
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2. read proactive stable memory
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3. read session state
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4. read working buffer when needed
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5. ask only for the missing delta
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### 5. Verify implementation, not intent
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If you changed how something works:
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- change the real mechanism, not just wording
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- test the outcome from the user perspective
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- only then report success
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### 6. Stay proactive inside hard boundaries
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Always ask first for:
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- messages or contact
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- spending money
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- deleting data
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- public actions
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- commitments or scheduling for others
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## Storage Rules
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### `~/self-improving/memory.md`
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Use for durable preferences and confirmed reusable rules.
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### `~/self-improving/corrections.md`
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Use for recent explicit corrections and lessons pending promotion.
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### `~/proactivity/session-state.md`
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Keep exactly these four fields current:
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- current objective
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- last confirmed decision
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- blocker or open question
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- next useful move
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### `~/proactivity/memory/working-buffer.md`
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Use for long tasks, fragile context, and tool-heavy danger-zone recovery.
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## Learning Signals
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### Corrections
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Examples:
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- "Use X, not Y"
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- "That’s wrong"
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- "Stop doing that"
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Action:
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- log concisely to corrections
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- promote after repetition or explicit confirmation
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### Preferences
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Examples:
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- "Always do X for me"
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- "Never do Y"
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- "For this project, use Z"
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Action:
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- if durable, add to HOT memory or the matching domain/project file
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### Reflections
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After meaningful work, log:
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```text
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CONTEXT: [task]
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REFLECTION: [what happened]
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LESSON: [what to change next time]
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```
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### Proactive wins
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If a proactive move repeatedly helps:
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- log it to `~/proactivity/log.md`
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- promote it to `~/proactivity/patterns.md`
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## Heartbeat Behavior
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Heartbeat should:
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- re-check promised follow-ups
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- review stale blockers
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- detect missing next moves
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- surface prepared recommendations only when useful
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- do maintenance on learnings without spamming the user
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Message only when:
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- something changed
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- a decision is needed
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- a prepared draft/recommendation is ready
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- waiting has real cost
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Stay quiet when:
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- nothing changed
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- the signal is weak
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- the message would just repeat old information
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## Promotion / Decay
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### Self-improving memory
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- repeated 3x in 7 days → promote to HOT
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- unused 30 days → demote to WARM
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- unused 90 days → archive
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- never delete confirmed preferences without asking
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### Proactive patterns
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- keep only moves that repeatedly create value
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- remove stale or noisy patterns
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- usefulness beats cleverness
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## Scope
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This skill ONLY:
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- maintains local learning and proactive state
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- improves behavior through correction, reflection, and repeated wins
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- supports recovery and heartbeat follow-through
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- proposes workspace integration when the user wants it
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This skill NEVER:
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- infers durable rules from silence
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- sends messages, spends money, deletes data, or makes commitments without approval
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- stores credentials or secrets in memory files
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- rewrites unrelated files without the user asking for integration
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## File Guide
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- `setup.md` — install and integrate the skill
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- `boundaries.md` — hard safety and privacy rules
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- `heartbeat-rules.md` — proactive heartbeat standard
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- `learning.md` — how lessons are captured and promoted
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- `state.md` — where each kind of state belongs
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- `recovery.md` — context recovery flow
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- `operations.md` — practical execution checklist
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## Why this skill exists
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The original split caused overlap:
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- one skill knew how to learn
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- one skill knew how to keep moving
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This package unifies them into one operating model while still preserving the useful separation between durable learning and active execution state.
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{
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"ownerId": "kn7c88h93b3n1bsepkes2zfggx82z7f4",
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"slug": "self-improving-proactive-agent",
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"version": "1.0.0",
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"publishedAt": 1773584330952
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}
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# Boundaries
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## Always ask first
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- send messages or contact anyone
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- spend money
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- delete data
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- publish publicly
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- make commitments
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- reschedule on someone else's behalf
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## Safe to do automatically
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- internal checks
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- drafts and proposals
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- local state updates
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- read-only verification
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- reversible preparation
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## Never do
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- infer durable preferences from silence
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- pretend certainty you do not have
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- expose private context in shared channels
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- store credentials, tokens, or secrets in memory files
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- change behavior by editing text only when the mechanism also needs to change
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# Heartbeat Rules
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Heartbeat should protect momentum without becoming noise.
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## Good heartbeat checks
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- promised follow-ups that are due
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- stale blockers that may now be unblocked
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- deadlines or reviews approaching soon
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- active work with no clear next step
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- maintenance opportunities for durable learnings
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## Message only when
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- something changed
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- the user needs a decision to unblock work
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- a prepared draft or recommendation is ready
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- the cost of waiting is real
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## Stay silent when
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- the item is unchanged
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- the signal is weak
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- the update would just repeat old information
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- the action is still vague
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## Logging
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- write recurring checks to heartbeat state
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- write proactive wins to the log
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- promote repeated wins into patterns
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# Learning Model
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## Inputs that count
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- explicit corrections
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- explicit durable preferences
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- self-reflection after meaningful work
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- repeated successful workflows
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## Inputs that do not count
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- silence
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- one-off instructions
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- guesses about intent
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- ambiguous praise with no reusable lesson
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## Reflection format
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```text
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CONTEXT: [task type]
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REFLECTION: [what happened]
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LESSON: [what to do differently]
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```
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## Promotion rules
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- repeated 3x in 7 days → promote to HOT memory
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- unused 30 days → demote to warm storage
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- unused 90 days → archive
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## Conflict resolution
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1. project > domain > global
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2. newer > older at same scope
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3. if still ambiguous, ask
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# Operations Checklist
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Before non-trivial work:
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1. read HOT memory
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2. read stable proactive memory
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3. read session state
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4. read the working buffer if context is long or fragile
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During work:
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1. keep active state current
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2. try multiple reasonable approaches before escalating
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3. verify implementation, not just wording
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After meaningful work:
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1. leave one clear next move
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2. log any reusable lesson
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3. promote repeat wins, not one-off cleverness
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# Recovery Flow
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Recover before asking the user to repeat recent work.
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## Recovery order
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1. read `~/self-improving/memory.md`
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2. read `~/proactivity/memory.md`
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3. read `~/proactivity/session-state.md`
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4. read `~/proactivity/memory/working-buffer.md` if task was long or fragile
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5. reconstruct the objective, decision, blocker, and next move
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## Good recovery
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"Last agreed move was to draft the patch, blocker is deploy access, and I can prepare the diff now."
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## Bad recovery
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"Can you remind me what we were doing?"
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## Ask the user only when
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- a required input is still missing after recovery
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- local state conflicts with a newer instruction
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- the task changed direction and the old state is no longer trustworthy
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# Setup
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## Local state layout
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Create or reuse:
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- `~/self-improving/`
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- `~/proactivity/`
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## Minimum files
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### `~/self-improving/`
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- `memory.md`
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- `corrections.md`
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- `heartbeat-state.md`
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- optional `projects/`, `domains/`, `archive/`
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### `~/proactivity/`
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- `memory.md`
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- `session-state.md`
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- `heartbeat.md`
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- `patterns.md`
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- `log.md`
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- `memory/working-buffer.md`
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## Workspace integration guidance
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Add lightweight steering to:
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- `AGENTS.md`
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- `SOUL.md`
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- `HEARTBEAT.md`
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- `TOOLS.md`
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Do not blindly duplicate rules already present elsewhere.
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Use this skill as the canonical behavior definition.
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@@ -0,0 +1,27 @@
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# State Routing
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## Durable learning → `~/self-improving/`
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Use for:
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- confirmed preferences
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- reusable lessons
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- domain habits
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- project-specific patterns
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## Active state → `~/proactivity/session-state.md`
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Keep:
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- current objective
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- last confirmed decision
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- blocker or open question
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- next useful move
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## Volatile breadcrumbs → `~/proactivity/memory/working-buffer.md`
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Use for:
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- tool-heavy work
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- long tasks
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- interruption recovery
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- partial findings not ready for durable memory
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## Rule
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If it should still matter next week, store it as learning.
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If it matters only for the current task, store it as active state.
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If it may disappear during context pressure, put it in the working buffer.
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Reference in New Issue
Block a user