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note_capture

Capture durable Markdown notes into an Obsidian vault, merging with existing notes when a matching title is found so you avoid duplicates and keep knowledge organized.

Instructions

Write one durable note into the Obsidian vault.

Search first with note_search: if a note on this subject already exists, calling this with the same title folds the new material into it under a dated update heading rather than creating a duplicate. Nothing already in the file is removed.

Note structure by kind:

{structure}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNoMarkdown body using the sections for this kind.
kindYesconcept | decision | lesson | question | project
tagsNoLowercase topic tags.
titleYesShort, specific, reusable as a wiki-link target.
sourceNoClient name, e.g. 'claude-code'.
relatedNoTitles of related notes.
summaryYesOne or two sentences stating the point.
projectsNoProject names this relates to.
log_to_dailyNoAlso link this from today's daily note.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden. It discloses that the tool writes durably, folds updates under dated headings, and never removes existing content. It could also mention the log_to_daily side effect and return behavior, but the disclosed update semantics go well beyond a minimal description.

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

Conciseness3/5

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

The prose is front-loaded and generally concise. However, the unresolved '{structure}' placeholder makes the description feel incomplete rather than intentionally tight, which prevents a higher score.

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 the core capture and update flow, and the rich schema covers parameters. But for a 9-parameter, no-annotation tool, it omits notable side effects such as the default log_to_daily behavior, and the placeholder for per-kind structure is not filled in.

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 description coverage is 100%, so the baseline is 3 and the schema already explains all nine parameters. The description adds only a little semantic context, such as 'same title' causing update behavior, but nothing substantial beyond what the schema provides.

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 opens with a specific verb-resource pair: 'Write one durable note into the Obsidian vault.' It also clarifies the update-vs-duplicate behavior, which distinguishes it clearly from the read/search siblings.

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 explicitly instructs agents to search first with note_search and explains what happens when a note with the same title already exists. It does not enumerate all alternatives or give a hard 'do not use when' rule, but the guidance is actionable and sufficient.

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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