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yanxue06

obsidian-mcp

by yanxue06

Run a Dataview DQL query

query_dataview

Execute Dataview DQL queries (LIST, TABLE, TASK) against an Obsidian vault to retrieve structured note data based on tags, dates, or metadata, enabling precise answers to complex questions like 'all incomplete projects sorted by due date'.

Instructions

Run a Dataview DQL query (LIST / TABLE / TASK) against the vault. Requires the Dataview plugin installed in the vault. Powerful for structured questions like 'all notes tagged #project where status != done sorted by due date'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dqlYesA Dataview DQL query string, e.g. TABLE status, due FROM #project WHERE status != "done" SORT due ASC
Behavior3/5

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

No annotations are provided, so the description carries full burden. It implies read-only behavior by calling it a query, but does not explicitly confirm no side effects, performance characteristics, or error handling (e.g., if plugin missing). The plugin requirement is noted, which is helpful.

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 efficiently convey purpose, prerequisite, and usage. No redundancy or unnecessary detail. Front-loaded with the core action.

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

Completeness3/5

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

The description covers purpose and prerequisite but omits any mention of return values or output format. Since there is no output schema, the description should ideally indicate what the tool returns (e.g., matching notes). The example is helpful but incomplete.

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?

With 100% schema coverage, the description adds value by giving a concrete example of the dql parameter. This clarifies the expected format beyond the schema's generic 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?

The description clearly states the tool runs Dataview DQL queries (LIST/TABLE/TASK), specifies the resource ('vault'), and provides an example. This distinguishes it from sibling tools like search_vault, which are not Dataview-specific.

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 mentions the prerequisite (Dataview plugin installed) and gives a use case example. However, it does not explicitly state when not to use it or suggest alternatives, though no direct alternative exists among siblings.

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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