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생산성 및 협업 · SKILL.md

Archive

Archive

Capture and preserve content as intelligent snapshots with semantic search, automatic extraction, and proactive resurfacing.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: Archive slug: archive version: 1.0.0 description: Capture and preserve content as intelligent snapshots with semantic search, automatic extraction, and proactive resurfacing. homepage: https://clawic.com/skills/archive metadata: clawdbot: emoji: 📦 requires: bins: [] os: - linux - darwin - win32 displayName: Archive

Architecture

Archive storage lives in ~/Clawic/data/archive/ with tiered structure. See memory-template.md for setup.

~/Clawic/data/archive/
├── memory.md          # HOT: recent items, ≤100 lines
├── index.md           # Topic/tag index
├── items/             # Individual archived items
├── projects/          # Per-project collections
└── history.md         # Search/access history

Quick Reference

TopicFile
What to capturecapture.md
Search patternssearch.md
Resurfacing rulesresurface.md

Core Rules

1. Capture Complete, Not Just Links

When user sends something to archive:

  • Extract full content (not just URL)
  • Generate 2-3 line summary
  • Identify key quotes/data points
  • Ask: "What's this for?" — store the WHY alongside the WHAT
  • Assign semantic tags based on content + user history

2. Content Types

TypeWhat to extract
Article/webpageFull text, author, date, key quotes
Video (YouTube)Title, creator, duration, timestamps mentioned
Tweet/threadFull text, author, context, media
PDF/paperTitle, authors, abstract, cited references
ImageDescription, source, context given
Idea/noteRaw text + timestamp + related items

3. Storage Structure

Each archived item stored as:

items/{date}_{slug}.md
---
type: article
url: original-url
archived: 2026-02-16
why: "research for pricing strategy"
tags: [pricing, saas, strategy]
project: clawmsg
---
## Summary
...
## Key Points
...
## Full Content
...

4. Semantic Search

User can ask naturally:

  • "What did I save about X?" → search by concept
  • "That article about pricing from last month" → fuzzy time + topic
  • "Everything for project Y" → project filter
  • "Papers by author Z" → metadata search

NEVER require exact keywords. Match by meaning.

5. Proactive Resurfacing

When user works on a topic:

  • Check if archived items relate
  • Surface ONLY if genuinely relevant (max 1-2 per session)
  • Include context: "You saved this 3 months ago when researching X"

6. Never Delete Without Asking

  • Old items → mark as "possibly outdated", don't delete
  • Duplicates → merge, keep both URLs
  • Project closed → archive to cold storage, don't remove

7. Differentiation from Other Skills

This skillWhat it doesNOT this
archivePreserves external content as snapshotsmemory (agent context)
archiveCaptures full content for permanencebookmark (just URLs)
archiveStores raw materialsecond-brain (processed knowledge)
archiveImmutable snapshotspkm (evolving notes)

Scope

This skill ONLY:

  • Stores content user explicitly sends to archive
  • Searches within archived content
  • Surfaces related items when contextually relevant

This skill NEVER:

  • Monitors or observes without explicit request
  • Deletes content without confirmation
  • Modifies original archived content
  • Accesses external services without user action

Data Storage

All data in ~/Clawic/data/archive/. Create on first use:

mkdir -p ~/Clawic/data/archive/items ~/Clawic/data/archive/projects
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