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LucasRocha179

mcp-vault-reader

memory_write_note

Store knowledge, user preferences, and project context by creating or updating markdown notes in the persistent memory vault. Supports wikilinks and tags for cross-referencing.

Instructions

Creates or updates a markdown note in the persistent memory vault. Use this to store knowledge, user preferences, project context, decisions, and any information worth remembering across sessions. Supports Obsidian-compatible wikilinks [[Like This]] and #tags for cross-referencing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesRelative path for the note (e.g., 'projects/my-app.md', 'preferences.md'). Folders will be created automatically. Must end in .md.
tagsNoOptional tags for categorization (without '#' prefix).
titleNoTitle of the note. Used as frontmatter title.
sourceNoOptional context about where this knowledge came from (e.g., 'code review session', 'user preference').
contentYesMarkdown content of the note body. Supports wikilinks and tags.
Behavior3/5

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

No annotations are provided, so the description must disclose behavior. It mentions the persistent vault and cross-session storage, and implies mutation via 'creates or updates.' However, it does not describe what happens when an existing note is updated (overwrite vs merge), or whether the operation is reversible. This is a notable gap for a mutation tool without annotation safety hints.

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 two sentences, front-loaded with the core action, followed by usage guidance and feature highlights. Every sentence adds value; there is no redundancy or fluff.

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, usage, and key features, and the schema thoroughly documents parameters. However, it lacks information about return values and precise update semantics, and there is no output schema or annotations to fill these gaps. For a write tool, this is acceptable but not fully complete.

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%, with detailed descriptions for all 5 parameters. The tool description adds little beyond the schema; it repeats that content supports wikilinks and tags, which is already in the schema. Baseline of 3 applies as the schema does the heavy lifting.

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 'Creates or updates a markdown note in the persistent memory vault,' specifying the verb, resource, and scope. It distinguishes from siblings like memory_delete_note by focusing on write/update, and lists concrete use cases that add clarity.

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 says 'Use this to store knowledge, user preferences, project context, decisions, and any information worth remembering across sessions,' providing clear when-to-use context. It does not mention alternatives or exclusions, but the context is sufficient for typical use.

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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