Works with the AI Agents you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+21 more

    Second Brain Obsidian Vault AI Assistant

    2

    Organize, link, and maintain Obsidian vaults with automated metadata management and MOC generation.

    $9.99

    Secure checkout via Stripe

    Money-back guarantee

    Converts to your local currency at checkout

    Security scanned
    Second Brain Obsidian Vault AI Assistant

    Second Brain Obsidian Vault AI Assistant

    Example session with this skill installed

    I'm uploading 3 notes about 'Vector Databases'. Can you audit them for duplicates, suggest a consistent frontmatter schema, and create a hub note to connect them?

    • Read your context and instructions
    • Compiled the second brain obsidian

    I have analyzed the provided notes: Vector_DB_Basics.md, Pinecone_Setup.md, and Milvus_vs_Weaviate.md. There is significant overlap between the Basics note and the comparison note regarding indexing strategies.

    Obsidian Vault Audit & Hub Proposal

    Metadata Schema Recommendation

    To keep your vector database research consistent, I recommend the following YAML frontmatter:

    title: Vector Databases
type: resource/research
status: active
tags:
  - machine-learning
  - databases
  - infrastructure
updated: 2024-05-20

    Proposed Hub Note: [[Vector Databases MOC]]

    
# Vector Databases MOC

## Overview
A Map of Content covering architecture, implementation, and comparisons of vector search engines.

## Foundational Knowledge
- [[Vector_DB_Basics]] — Core concepts of embeddings and similarity search.

## Implementations
- [[Pinecone_Setup]] — Managed service configuration and API usage.
- [[Milvus_vs_Weaviate]] — Comparison of open-source self-hosted options.

## Potential Connections
- Check [[LLM Ops]] for deployment patterns.
- Connect to [[RAG Architecture]] for retrieval flows.
    IssueDescriptionRecommendation
    Duplicate ContentHNSW algorithm explained in two files.Centralize HNSW logic in [[Vector_DB_Basics]].
    Missing LinkPinecone_Setup mentions indexing but doesn't link to basics.Add `[[Vector_DB_Basics
    Tag InconsistencyOne note uses #ml and another #machine-learning.Standardize on #machine-learning.

    Next steps

    1. Create the Vector Databases MOC.md file with the content above.
    2. Update the frontmatter in the three source notes for better Dataview compatibility.
    3. Move HNSW technical details from the comparison note to the basics note to reduce redundancy.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    The problem

    Building a personal knowledge base is easy, but maintaining it is hard. Most Obsidian vaults eventually become a graveyard of disconnected Markdown files, broken Wikilinks, and inconsistent metadata that makes retrieval impossible.

    What it does

    • Analyzes vault structure to identify orphan notes, duplicate concepts, and missing Wikilink connections.
    • Generates structured notes with valid YAML frontmatter following existing vault conventions.
    • Creates Maps of Content (MOCs) and hub notes to organize sprawling topics without forcing rigid folder hierarchies.
    • Refactors messy notes by improving Markdown hierarchy and normalizing tags while preserving original content.
    • Synthesizes answers from supplied vault files, citing specific note paths and identifying knowledge gaps.

    Frameworks & tools

    Obsidian, Markdown, YAML Frontmatter, Wikilinks.

    Why this beats prompting it yourself

    Generic LLMs often hallucinate note links or ignore your specific metadata schema. This skill is hard-coded to respect Obsidian-native conventions like Wikilinks and frontmatter standards, ensuring every suggestion is a valid, reversible edit that fits your existing workflow.

    Use cases

    • Perform a vault audit to find and link orphan notes.
    • Convert a raw web clip into a structured permanent note with relevant metadata.
    • Generate a Map of Content for a complex research topic using existing notes.
    • Standardize tagging and frontmatter across a collection of project files.

    Known limitations

    Cannot access local vault files directly without an authorized integration or manual file uploads. Link validation is limited to the context provided in the current session.

    Requires manual file provision or authorized integration to see vault content. Link validation is restricted to provided context. Cannot perform semantic search without external tool support.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

    Reviews

    No reviews yet

    Be one of the first to try it. Every listed skill goes through the trust checks below.

    Security scanned

    Checked by our 8-point scan before listing

    Fresh listing

    Recently published to Agensi

    Money-back guarantee

    Doesn't do what its page promises? You get your money back.

    Trust & safety

    Security scan

    Security scan passed 1 month ago

    Permissions

    No special permissions declared or detected

    Listed1 month ago

    What's inside

    Frequently Asked Questions

    This skill acts as an intelligent architect for your vault, automating the creation of Maps of Content (MOCs), fixing broken Wikilinks, and standardizing YAML frontmatter to prevent your knowledge base from becoming disorganized.

    No, the skill is designed to enhance your content by improving Markdown hierarchy and metadata; it does not delete or overwrite your original notes without your direction.

    Yes, the skill is hard-coded to recognize and generate Obsidian-specific syntax, including [[Wikilinks]], #tags, and YAML frontmatter, ensuring all output is native to the Obsidian environment.

    You will receive the AI agent skill configuration, a set of best-practice templates for metadata, and a guide on how to integrate the skill with your preferred AI agent platform.

    Since the skill cannot browse local drives directly, you will need to provide the relevant Markdown files or folder structures to your AI agent interface to allow it to analyze and refactor them.

    Buyers receive lifetime access to the current version of the skill, including any logic refinements or compatibility updates released to address changes in Obsidian's core Markdown standards.

    New in Productivity