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Auto Memory Curation

Automatically analyzes messages for important information and stores it in the right memory files. Runs silently on every message. Filters noise, captures me...
自动分析消息中的重要信息并将其存入相应的记忆文件;静默运行于每条消息,过滤噪音,捕获...
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数据分析 clawhub v1.0.0 1 版本 100000 Key: 无需
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概述

Auto Memory Curation Skill

Overview

Silently analyze every message for important information and store it appropriately. Reduces manual memory management while building rich context over time.

How It Works

Trigger

  • Runs on every message (silently)
  • No user activation needed

Analysis Pipeline

Step 1: Filter Noise

Skip these message types:

  • Greetings (hi, hello, hey)
  • Thanks/thanking
  • Acknowledgments (ok, sure, yes, yeah)
  • Questions without context
  • Single word responses
  • Bot commands

Step 2: Categorize

For non-noise messages, categorize:

CategoryWhat to look forStore in
--------------------------------------
FactNew info about user, projects, preferencesMEMORY.md
DecisionChoices made, conclusions reachedmemory/YYYY-MM-DD.md
PreferenceLikes, dislikes, style preferencesUSER.md
IdeaRandom thoughts, inspiration, conceptsmemory/topics/ideas.md
LearningLessons, insights, discoveriesmemory/topics/lessons.md
ProjectProject updates, progress, blockersmemory/projects/
GoalGoals, targets, milestonesmemory/topics/goals.md
ErrorMistakes, corrections to avoidmemory/topics/anti-patterns.md
CommitmentPromises I make, tasks to dotasks.md

Step 3: Extract & Store

  • Extract the key information
  • Add timestamp reference
  • Store in appropriate file
  • Use append mode (never overwrite)

Guidelines

What to Capture

  • New facts about Vini (name, preferences, goals)
  • Project updates or decisions
  • Ideas for future projects
  • Learning insights
  • Corrections (what doesn't work)
  • Commitments I make

What to SKIP

  • Passwords, secrets, API keys
  • Trivial acknowledgments
  • Basic confirmations
  • Questions I'm asking
  • Technical errors that are fixed

Quality Rules

  1. Be selective - Don't store everything
  2. Be concise - One sentence per memory
  3. Be contextual - Include enough info to understand later
  4. Be accurate - Don't paraphrase incorrectly
  5. Never duplicate - Check if already stored

Format

## [Category] - YYYY-MM-DD

- **[What]:** [Brief description]
  *Context:* [Why it matters or relevant message]

Examples

User says:

> "I prefer concise messages, no filler words"

Stored in USER.md:

> ## Preference - 2026-03-06

> - Communication: Prefers concise messages, no filler words


User says:

> "Let's build a landing page for the consultancy inspired by Nexus AI"

Stored in memory/2026-03-06.md:

> ## Decision - 2026-03-06

> - Consultancy: Will use Nexus AI style for landing page


User says:

> "I realized I work better with visual examples first, then theory"

Stored in MEMORY.md:

> ## Learning - 2026-03-06

> - Learning Style: Visual examples first, theory after


Testing

Periodically review stored memories to calibrate:

  • Am I capturing too much noise?
  • Am I missing important things?
  • Are categories correct?

Adjust based on quality of accumulated memories.

Override

User can disable or adjust this skill at any time by saying:

  • "Don't store that"
  • "Clear recent memories"
  • "Adjust memory curation"

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-03-30 14:01 安全 安全

安全检测

腾讯云安全 (Keen)

安全,无风险
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腾讯云安全 (Sanbu)

安全,无风险
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