obsidian workflows & second brain methodology

Obsidian Workflows & Second Brain Methodology

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Install skill "obsidian workflows & second brain methodology" with this command: npx skills add kriscard/kriscard-claude-plugins/kriscard-kriscard-claude-plugins-obsidian-workflows-second-brain-methodology

Obsidian Workflows & Second Brain Methodology

Actionable guidance for building and maintaining a second brain in Obsidian. This skill focuses on workflows and decisions — not PARA theory (Claude already knows that).

PARA Quick Reference

Organize by actionability, not topic:

Category What Goes Here Review Cadence

Projects Active work with clear endpoints Weekly

Areas Ongoing responsibilities, no endpoint Monthly

Resources Reference materials, future interest Quarterly

Archives Completed/inactive from above Annually

When in doubt: "Does this have a deadline or clear outcome?" Yes = Project. "Is this an ongoing responsibility?" Yes = Area. Otherwise = Resource.

Key Workflows

Capture (minimize friction)

  • Drop everything into Inbox

  • Minimal formatting — structure comes later

  • One idea per note (atomic)

  • Include source and why it matters

  • Tag as #inbox for processing

Inbox Processing (weekly review, 30 min)

For each inbox note, decide:

  • Delete — Not useful, was impulse capture

  • Archive — Useful reference but no action needed now

  • Elaborate — Add context, links, tags, then move to PARA category

Target: empty inbox weekly.

Review Cadences

Cadence Time What to Do

Daily 5 min Create daily note, review active projects, process quick captures

Weekly 30 min Process inbox completely, review all projects, update areas, clean loose ends

Monthly 1 hour Review areas, archive completed projects, check OKRs/goals, update MOCs

Quarterly 2 hours Strategic review, archive inactive resources, consolidate tags, adjust PARA

Linking Rules

The 2-Link Rule

Every new note links to at least 2 existing notes. This prevents orphans and forces context-building. Ask "What does this connect to?" before saving.

MOCs vs Dashboards

Keep these separate — they serve different purposes:

MOCs (Maps of Content) — Hand-curated navigation. Each link includes why it's connected. Create when a topic has 10+ related notes. Updated intentionally, not constantly.

Dashboards — Auto-generated views (dataview queries). Show recent activity, stats, tasks. No manual curation needed.

When to Create a MOC

  • Topic has 10+ related notes

  • Need an overview of a knowledge area

  • Connecting notes across multiple PARA categories

  • Want curated navigation (not just a flat list)

Evergreen Notes (3-Layer Pattern)

Concept notes that grow over time:

Layer 1 — Definition: What is this concept? Your own words, core explanation. Rarely changes.

Layer 2 — Related: How does this connect? 2-5 links with reasons:

Related

  • [[Event Loop]] — closures power async callbacks
  • [[Garbage Collection]] — closures affect GC behavior

Layer 3 — Encounters: Real-world usage added over time:

Encounters

2026-02-05 - Debugging closure scope issue

Discovered that closures in a forEach loop captured the loop variable by reference. Link: [[TIL 2026-02-05]]

Use Outgoing Links panel to discover connections you missed.

Progressive Summarization

Refine notes just-in-time (when you revisit them, not when you capture):

  • Capture — Full source material

  • Bold — Key passages (10-20% of content)

  • Highlight — Within bold (10-20% of that)

  • Summarize — 2-3 sentence executive summary at top

  • Remix — Create new output from distilled knowledge

Apply layers only when you return to a note for a specific purpose. Don't process everything upfront.

Integration with Plugin Commands

This skill informs all plugin commands and agents:

  • /daily-startup uses daily note workflow patterns

  • /process-inbox implements inbox processing workflow

  • /review-okrs applies review cadences to goal tracking

  • /maintain-vault ensures link health and organization

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

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