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Epochal-dev

Open Notebook MCP Server

by Epochal-dev

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Find relevant notes and sources by querying with vector or text search. Optionally limit to a specific notebook and control the number of results.

Instructions

Search content using vector or text search.

Args:
    query: Search query
    type: Search type ('vector' or 'text')
    notebook_id: Optional notebook ID to limit search
    limit: Maximum number of results (1-50)

Returns:
    Search results

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
typeNovector
notebook_idNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations provided, the description bears full burden for behavioral disclosure. It only states basic functionality and returns 'Search results', without mentioning safety (read-only), performance, side effects, or error handling.

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

Conciseness4/5

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

The description is concise, uses a standard docstring format with Args and Returns sections, and front-loads the purpose. Every sentence is useful with no wasted words.

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?

Given the 4 parameters and lack of annotations, the description is adequate but not rich. It explains each parameter simply but omits details like search behavior, ranking, or pagination. The output schema likely covers return structure, so missing return explanation is acceptable.

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 0%, so the description must compensate. It provides brief but meaningful explanations for each parameter (e.g., enum values for 'type', default for 'limit'), adding value beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches content using vector or text search. It specifies the main action and resource, but does not explicitly differentiate from sibling tools like 'ask_question' or 'search_capabilities', which might be related.

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?

No guidance on when to use this tool versus alternatives (e.g., ask_question, search_capabilities). There is no discussion of when to use vector vs text search or what prerequisites exist.

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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