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index_all

Rebuild the local SQLite index of all Markdown files, metadata, and links after reorganizing notes. Optionally compute vector embeddings for semantic classification when an embedding provider is available.

Instructions

Scan the whole Markdown vault and rebuild the local SQLite index of files, metadata, and graph links. Use this after adding, moving, or reorganizing notes outside NOUZ. It is safe to run repeatedly and reports missing parent links. With with_embeddings=true it also updates vector embeddings for semantic classification, which is slower and requires an embedding provider. This tool indexes data; it is not a search tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
with_embeddingsNoIf true, compute embeddings for all files (slower, requires LM Studio/Ollama). Default false.
Behavior4/5

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

No annotations present, but description discloses important behaviors: safe to run repeatedly (idempotent), reports missing parent links, and embedding impacts (slower, external dependency). Covers safety and side effects adequately.

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?

Two sentences with no redundancy. Front-loaded with main action and purpose. Every sentence adds new information. Efficient and well-structured.

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

Completeness4/5

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

For a moderate-complexity indexing tool, description covers purpose, usage, safety, and parameter behavior. Lacks explicit return value details, but 'reports missing parent links' implies output. Overall adequate given no output schema and single parameter.

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

Parameters4/5

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

Schema covers 100% of param with description. Tool description adds value by explaining the embedding parameter's purpose ('semantic classification') and additional context ('slower, requires embedding provider'), enriching the schema description.

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?

Clearly states it scans the vault and rebuilds an SQLite index of files, metadata, and graph links. Differentiates itself from search tools explicitly ('This tool indexes data; it is not a search tool'). Specifies when to use (after adding, moving, reorganizing notes).

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?

Provides clear context for when to use: after note changes. Mentions it's safe to repeat and reports missing parent links. Distinguishes embedding use case (slower, requires provider). However, does not explicitly name alternatives among sibling tools for similar tasks.

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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