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glean
by robabby
Documentation website for AI-ready Obsidian vaults with downloadable starter templates
⭐ 0🍴 0📅 Jan 13, 2026
SKILL.md
name: glean description: Surface emergent patterns and insights from the AI-ready vault memory system. Use periodically to discover connections between memories, identify recurring themes, and generate meta-insights that aren't obvious from individual memories.
Glean
Surface emergent patterns and insights from memory.
Purpose
Individual memories capture discrete information. Gleaning reveals:
- Connections between seemingly unrelated memories
- Recurring themes or patterns
- Evolution of thinking over time
- Gaps or contradictions in stored knowledge
- Meta-insights that emerge from the collection
Workflow
-
Load memories for analysis
- If $ARGUMENTS provided, focus on that domain
- Otherwise, analyze across all memory types
- Prioritize recent and high-importance memories
-
Identify patterns
- Recurring concepts across memories
- Related decisions or approaches
- Evolving understanding of topics
- Clusters of related information
-
Surface insights
- What themes emerge?
- What connections weren't obvious?
- What contradictions exist?
- What gaps should be filled?
-
Optionally store meta-memories
- Patterns discovered can become new memories
- Type: Usually Strategic or Procedural
Analysis Dimensions
| Dimension | Questions |
|---|---|
| Temporal | How has thinking evolved? What changed? |
| Conceptual | What themes recur? What clusters form? |
| Contradictions | Where do memories conflict? |
| Gaps | What's missing? What should be captured? |
| Connections | What links across domains? |
Parameters
$ARGUMENTS(optional): Domain or topic to focus analysis on
Default Paths
Analyzes memories at: Areas/AI/Memory/
Related Skills
/recall {terms}- Search for specific memories/remember- Store patterns discovered as new memories/reflect- Session-end memory consolidation
Output Format
Patterns Observed:
- List of 3-5 patterns or themes
Connections Found:
- Links between memories that weren't explicitly made
Insights:
- 1-3 meta-observations about the memory collection
Recommendations:
- Suggested memories to create, update, or consolidate
Example
User: /glean ai-ready-vault
Response: "Gleaning patterns from AI Ready Vault memories...
Patterns Observed:
- Composability is a recurring theme—skills, tiers, teaching approach all emphasize modularity
- 'Let the work speak' appears in both personal branding and product design decisions
- Education-first positioning across all strategic decisions
Connections Found:
- Teaching pattern (show→problem→conceptual) mirrors the product evolution (demo→pain→solution)
- Skills library concept directly enables the 'incremental adoption' goal
Insights:
- The project philosophy is internally consistent—same principles apply at multiple levels
- Strong bias toward empowering users vs. prescribing solutions
Recommendations:
- Consider creating a 'design principles' memory that captures the recurring themes
- The composability pattern could become a procedural memory for future projects"
Score
Total Score
50/100
Based on repository quality metrics
✓SKILL.md
SKILL.mdファイルが含まれている
+20
○LICENSE
ライセンスが設定されている
0/10
○説明文
100文字以上の説明がある
0/10
○人気
GitHub Stars 100以上
0/15
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3ヶ月以内に更新がある
0/10
○フォーク
10回以上フォークされている
0/5
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オープンIssueが50未満
+5
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+5
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1つ以上のタグが設定されている
0/5
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