본문으로 건너뛰기
cccskills
무료GitHub에 공개

agentic-zettelkasten

Structured Zettelkasten workflow for AMD — observe, draft, enrich, retrieve, decide, preview, write, verify. Produces high-quality atomic knowledge cards with deliberate linking.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(1)

  • SKILL.md6.4 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Agentic Zettelkasten Skill

A structured Zettelkasten protocol for Advanced Memory that produces high-quality atomic knowledge cards through deliberate retrieval, enrichment, and explicit link decisions.

This skill replaces ad-hoc note-taking. Every card written through this workflow is an atomic insight in your own words, with [[wikilinks]] embedded in sentences explaining the relationship — not a bare tag list.

Core Principles (Luhmann's Method)

  1. Atomicity — One insight per card. If you have two ideas, write two cards.
  2. Own words — Distill and rephrase. Copy-paste = no understanding (Feynman test).
  3. Links in context — [[links]] must appear in sentences explaining the relationship. Good: "This contradicts [[jwt-migration]] — stateless tokens can't be revoked." Bad: "Related: [[jwt-migration]]"
  4. Retrieve before write — Always search for existing cards first. Never create duplicates.
  5. Preview before mutate — Show planned changes before writing anything.

Tools Available

ActionAMD Tool
Search existing knowledgeadn_search(operation="rag", prompt="...") or adn_search(operation="query", text="...")
Read a cardadn_notes(operation="read", identifier="...")
Write a new cardadn_notes(operation="write", title="...", content="...", folder="...")
Edit existing cardadn_notes(operation="edit", identifier="...", mode="append", content="...")
Check recent activityadn_nav(operation="recent", timeframe="7d")
Analyze knowledge gapsadn_zettel(operation="analyze")
Get link suggestionsadn_zettel(operation="connect")

Workflow

Step 1: Observe — What did we learn?

After completing a task, identify reusable insights. Skip if the content is:

  • Temporary or session-specific (in-progress work, task state)
  • Obvious or well-known (standard library usage, common patterns)
  • Not reusable across future sessions

If nothing is worth remembering, stop here. This is a quality gate, not a formality.

Step 2: Draft — One atomic card per insight

For each insight, draft exactly one card:

  • Title: Short noun phrase (≤60 chars, kebab-case slug). Descriptive, not clever.
  • Body: One atomic insight in your own words. 3-8 sentences. Include:
    • What the insight IS
    • Why it matters (context)
    • When it applies (boundary conditions)
    • A concrete example or counterexample

If you need more than 8 sentences, you probably have two insights. Split them.

Step 3: Enrich — Proposed metadata

---
title: <Short Noun Phrase>
created: <YYYY-MM-DD>
category: <one category: developer|researcher|writer|knowledge-worker|etc.>
tags: [<3-5 comma-separated categories>]
keywords: [<3-8 salient terms>]
---

Step 4: Retrieve — Search before writing

Search for related existing cards using at least TWO queries:

adn_search(operation="rag", prompt="<topic keywords>", limit=5)
adn_search(operation="query", text="<exact term>", search_type="title")

Read the top candidates that look relevant:

adn_notes(operation="read", identifier="<slug>")

Limits to avoid runaway retrieval:

  • Max candidate searches: 3
  • Max cards read: 10

Step 5: Decide — create, update, or skip

Choose exactly one action per insight:

ActionWhen
createNo existing card covers this insight. Embed [[wikilinks]] to related cards.
updateExisting card covers the same insight but lacks new detail.
skipInsight is duplicate, too obvious, or not durable.

Rules:

  • Links must be chosen by reading candidate cards, not from embedding scores.
  • Updating is allowed only after preview (Step 6).
  • If in doubt between create and update: create. It's safer to have two cards than to corrupt one.

Step 6: Preview — Show planned changes

Before writing, produce a preview:

Planned memory changes:
- CREATE: python-asyncio-gotcha (title: "Asyncio gather() doesn't guarantee order")
  → links: [[task-queue-pattern]] because tasks run concurrently, not sequentially
  → metadata: category=developer, tags=python,async,concurrency
- UPDATE: task-queue-pattern — add note about gather() ordering pitfall
  → append: "Note: asyncio.gather() starts all tasks concurrently; results
    may arrive out of order. Use asyncio.as_completed() for ordered results."

Step 7: Write

Create new card:

adn_notes(operation="write",
  title="Asyncio gather() doesn't guarantee order",
  content="...",
  folder="developer",
  tags="python,async,concurrency")

Update existing card:

adn_notes(operation="edit",
  identifier="task-queue-pattern",
  mode="append",
  content="...")

Rules for writing:

  • Wikilinks go in body text, not just frontmatter
  • Every link has a "because" clause
  • Title must match slug (kebab-case)
  • Content is markdown with at least one [[wikilink]]

Step 8: Verify — Readback check

After writing, read the card back:

adn_notes(operation="read", identifier="<slug>")

Confirm:

  • Title and body match what was intended
  • All [[wikilinks]] are syntactically valid
  • Metadata frontmatter is complete (title, created, category, tags)
  • Body is in your own words (not copy-pasted)

Anti-Patterns

Don'tDo instead
Write 5 cards at once without retrievalOne card at a time, retrieve between each
Add [[links]] based on keyword overlapRead the target card, decide if the relationship is meaningful
Update a card without previewPreview first, then update
Use AI-generated content verbatimDistill and rephrase in your own words
Skip the verify stepAlways readback after writing
Create a "note dump" with 3 ideas in one cardSplit into atomic cards, one insight each
Use bare links like "See also: [[X]]"Embed in sentence: "This relates to [[X]] because..."

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Expert in groups, rings, fields, and algebraic structures with applications to cryptography and number theory

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

sandraschi/advanced-memory-mcp202026년 10월 13일 업데이트

Expert in Japanese honorific language covering 尊敬語・謙譲語・丁寧語 with deep understanding of situational usage, business contexts, and cultural nuances

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

sandraschi/advanced-memory-mcp202026년 10월 13일 업데이트

Use when planning, scaffolding, validating, or packaging Claude skills inside Advanced Memory MCP.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

sandraschi/advanced-memory-mcp202026년 10월 13일 업데이트

Master AI debate techniques with comprehensive counter-arguments against slop criticism, safety concerns, philosophical objections, and political rhetoric

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

sandraschi/advanced-memory-mcp202026년 10월 13일 업데이트

Master AI-integrated development environments with comprehensive coverage of Windsurf, Cursor, Antigravity, Zed, Cline, and FOSS newcomers, including intelligent usage patterns, cost optimization, and the evolution toward fully agentic development

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

sandraschi/advanced-memory-mcp202026년 10월 13일 업데이트

Expert in historical alchemy, Hermetic philosophy, and symbolic transformation from medieval to modern esoteric traditions

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

sandraschi/advanced-memory-mcp202026년 10월 13일 업데이트

sandraschi의 스킬 모두 보기

이 스킬의 문제 신고