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vault_health

Read-onlyIdempotent

Return health metrics and validation for Obsidian vaults. Detect drift in frontmatter, stale content, and broken links with optional usage analytics.

Instructions

Return vault health metrics, validation, and optional usage analytics.

Always emits the ## server identity block (version, python, vault path, backend presence, started_at) at the top.

Without parameters, returns a health summary for all projects. When checks are specified, runs drift detection (frontmatter, stale, links). When include_usage is True, appends tool usage analytics. When include_runtime is True, appends runtime metadata (uptime, tools, budget).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectNoProject slug to validate. Empty = all projects.
checksNoValidation checks to run. Empty = health summary only. Options: frontmatter, stale, links.
max_issuesNoMaximum validation issues to report. Default 50.
include_usageNoAppend vault tool usage analytics. Default False.
usage_daysNoUsage look-back window in days. Default 30.
include_runtimeNoAppend runtime metadata block. Default False.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Despite annotations already indicating readOnlyHint=true and idempotentHint=true, the description adds significant behavioral context: always emits server identity block, details on drift detection checks, and effects of boolean flags. No contradictions with annotations.

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 concise and well-structured, front-loading the main purpose then detailing parameter behavior in bullet-like prose. Every sentence adds value without redundancy.

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?

Given the tool's complexity and the presence of an output schema, the description sufficiently covers all modes and behaviors. It could mention expected response size or that it's a query-only tool, but overall it is complete for effective use.

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 description coverage is 100%, so baseline is 3. The description adds high-level semantics: explaining that empty checks gives health summary, checks run specific validations, and include_usage/runtime append blocks. This adds value beyond the schema's per-parameter descriptions.

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 explicitly states it returns vault health metrics, validation, and optional usage analytics. It distinguishes itself from sibling tools like vault_list or vault_query by focusing on health and drift detection. The verb 'Return' and resource 'health metrics and validation' are specific and clear.

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 clearly explains when to use different parameters: no parameters for health summary, checks for drift detection, include_usage for analytics, include_runtime for metadata. It does not explicitly state when to avoid this tool, but the context with sibling tools makes its purpose distinct.

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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