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Vault query

Skill Howie126313/obsidian-vault-kit/skills/vault-query

Claude Code plugin for full-lifecycle Obsidian knowledge management — vault lint, Karpathy-style query, Ebbinghaus spaced repetition, article ingestion, and GitHub sync.

Install
npx -y skills add Howie126313/obsidian-vault-kit --skill vault-query

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Karpathy-style vault query and synthesis system. Reads index.md to locate articles, synthesizes answers from multiple sources, and optionally writes high-value results back as new notes. Triggers: "/vault-query", "search vault", "find in notes", "query knowledge base"

SKILL.md

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Vault Query — Karpathy-Style Knowledge Synthesis

Based on the "compile, don't retrieve" philosophy: look up the index first, read full text to synthesize, write back high-value answers.

Workflow

Step 1: Environment Detection & Query Parsing

1a. Detect vault root — follow ../../_shared/common-steps.md "Vault Detection" section.

1b. Parse user query intent:

Extract from user input:

  • query: core question or keywords
  • scope: whether a directory scope was specified (e.g., user mentions a topic that maps to a configured directory)
  • depth: simple lookup ("which article covers X") vs deep synthesis ("compile everything about X")

Step 2: Index Lookup

2a. Read index.md:

Read("$VAULT_ROOT/index.md")

Scan all entries in index.md — titles, summaries, and tags — to find candidate articles related to the query (typically 3-8).

2b. Supplementary search:

index.md may miss content. Use Grep to supplement:

Grep("{keyword}", path="$VAULT_ROOT", glob="**/*.md")

Exclude results from .claude/, .git/, reviews/, index.md.

2c. Determine reading list:

Merge index lookup and Grep results, sort by relevance, finalize the list of articles to read in full.

Step 3: Deep Read & Synthesis

3a. Read relevant articles in full:

For each article on the reading list, use Read to get full text. Read in parallel for efficiency.

3b. Synthesize the answer:

Choose synthesis mode based on depth:

  • Simple lookup: list relevant articles and their key points, point the user to read directly
  • Deep synthesis:
    1. Extract key information from multiple articles
    2. Integrate into a complete knowledge picture, citing sources (see [[article-name]])
    3. Surface connections, contradictions, or complementary relationships between articles
    4. Identify knowledge gaps ("no article covers aspect Y of topic X")

Step 4: Write-Back Decision

After synthesizing, evaluate whether writing back is warranted:

Worth writing back:

  • Synthesized new insights across 3+ articles
  • Discovered undocumented connections between articles
  • The user's question reveals a knowledge gap worth filling
  • Produced a reusable comparison analysis or decision matrix

Not worth writing back:

  • Simple lookup ("which article covers X")
  • Answer comes entirely from a single article
  • One-off question

4a. If worth writing back, use AskUserQuestion to ask:

"This query produced valuable synthesized knowledge: {brief description}. Save as a new note? Suggested title: {title}, directory: {dir}/"

Upon user confirmation:

  1. Determine directory per the Directory Mapping Rules in ../../_shared/common-steps.md
  2. Search for bidirectional links per Bidirectional Link Search
  3. Write the new note with complete frontmatter:
    • title: synthesis note title
    • date: today's date
    • tags: 3-8 relevant tags
    • type: inferred per Type Inference Rules in ../../_shared/common-steps.md
    • confidence: cross-article synthesis is typically medium
    • related: source article list ("[[article-name]]" format)
    • summary: 1-3 sentence synthesis summary
    • source: "Vault Query synthesis"
  4. Update index.md: per the Index Update steps in ../../_shared/common-steps.md, append the new article to the corresponding section

Step 5: Report

Output to user:

  • Synthesized answer (with [[wikilink]] citations)
  • List of referenced articles
  • If written back, report the save location
  • If knowledge gaps were found, suggest topics to add

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