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validate_note

Validate note frontmatter against Lua type schemas, catching missing fields, type errors, and enum mismatches. Optionally auto-fix safe issues or filter by path, note type, and limit.

Instructions

Validate notes against Lua type definitions (frontmatter schema).

Runs mdv validate to check that note frontmatter conforms to the type definition schemas (required fields, types, enums, defaults).

Args: path: Specific note path to validate (relative to vault root). Omit to validate all notes. note_type: Only validate notes of this type (daily, task, project, etc.). fix: Auto-fix safe issues (missing defaults, enum case normalisation). limit: Maximum number of notes to validate.

Returns: Validation report with per-note errors and fixes applied.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fixNo
pathNo
limitNo
note_typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of disclosing behavior. It reveals the underlying command (`mdv validate`), the checks performed, the fix side effects ('Auto-fix safe issues', 'fixes applied'), and the return type. It could be stronger by explicitly warning that `fix: true` modifies notes, but the disclosure is largely adequate.

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?

The description is well-organized with a one-line purpose, an Args section, and a Returns note. It is concise, front-loaded with the core purpose, and every sentence adds useful information without fluff.

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?

All four parameters are documented, the behavioral scope is clear, and the return value is described even though an output schema exists. The description is complete enough for an agent to call the tool correctly without additional context.

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

Parameters5/5

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

Schema description coverage is 0%, and the input schema has no descriptions. The description compensates fully by explaining each parameter: path scope, note_type filtering, fix behavior, and limit. This adds clear operational meaning beyond the bare schema.

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 states a specific action ('Validate notes') against a clear resource ('Lua type definitions (frontmatter schema)'). It is immediately distinguishable from sibling tools like vault_lint or get_metadata because it names the validation target and the underlying command.

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

Usage Guidelines2/5

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

The description explains how to use the tool (optional path, note_type, fix, limit) but gives no guidance on when to choose validate_note over alternatives. There is no mention of when not to use it or which sibling tool might be more appropriate for related tasks.

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