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Index Vault for Semantic Search

index_vault
Idempotent

Index notes by generating heading-aware embeddings for semantic search and similarity lookups. Supports incremental updates and forced re-indexing for model changes.

Instructions

Build or refresh the embedding index used by search_semantic and find_similar_notes. Splits each note into heading-aware chunks, embeds them via the configured provider (Ollama by default, OpenAI optional), and persists the index to <vault>/.obsidian/cache/mcp-pro-embeddings.json. Incremental: notes whose content hash matches the prior pass are skipped. Use force: true to re-embed everything (e.g., after switching models). Emits progress notifications when the client subscribes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
forceNoIf true, re-embed every note even if its content hash matches the cached one.
folderNoRestrict the indexing pass to this folder. Notes outside the folder are left untouched.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds context beyond annotations: it splits notes into heading-aware chunks, embeds via configured provider, persists to a specific file, and emits progress notifications. Annotations already indicate idempotent and non-destructive, which align with description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences front-loaded with purpose, then process, incremental behavior, force usage, and progress notifications. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description fully explains the tool's behavior, side effects, and progress notifications. Annotations cover safety. Complete for the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers 100% of parameters with descriptions. The description adds minimal additional meaning beyond incremental behavior related to force. Baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool builds or refreshes the embedding index used by search_semantic and find_similar_notes. It specifies the verb (build/refresh) and resource (embedding index) and distinguishes it from sibling tools that consume the index.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains incremental behavior and when to use force (re-embed everything after model changes). The folder parameter restricts indexing. However, it does not explicitly mention when not to use this tool or alternatives beyond referencing search_semantic and find_similar_notes.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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