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viantonugroho11

@viantotech/mcp-storybook

get_story_context

Retrieve concise Storybook context for natural-language questions. Get relevant story and component details to answer queries.

Instructions

Retrieve concise Story Book context for a natural-language question.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
storyIdNo
maxResultsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior2/5

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

Since no annotations are provided, the description carries the full behavioral burden. 'Retrieve... context' implies a read operation, but the description does not disclose what shape the returned context takes, whether storyId scopes the retrieval, or how maxResults affects results.

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 a single sentence with no filler, front-loading the action and resource. Every word contributes to the core meaning, making it efficient and easy to parse.

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

Completeness2/5

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

Given no annotations, no output schema, and 0% parameter description coverage, the description is too thin to support reliable invocation. An agent cannot infer what 'context' consists of, what storyId and maxResults do, or what the response will look like.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description needed to explain the query, storyId, and maxResults parameters. It only clarifies that query is a natural-language question; the semantics of the optional storyId and maxResults parameters are left entirely to the schema's bare names and constraints.

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 states a specific action ('Retrieve') and object ('concise Story Book context') tied to a natural-language question, which gives a clear sense of what the tool does. It is not fully distinguished from siblings like search_stories or get_story_section, but the focus on 'context for a natural-language question' differentiates it from simple story or metadata retrieval.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'for a natural-language question' implies when the tool would be useful, but there is no explicit guidance about when to prefer it over alternatives like search_stories or get_story. No exclusions or sibling comparisons are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.