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krishna-goje

quicksight-mcp

by krishna-goje

create_bar_chart

Create a bar chart in an AWS QuickSight analysis sheet using a category column, value column, and aggregation to compare dataset values.

Instructions

Create a bar chart from simple parameters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYesDisplay title.
sheet_idYesThe sheet to add the chart to.
analysis_idYesThe QuickSight analysis ID.
orientationNoVERTICAL (default) or HORIZONTAL.VERTICAL
value_columnYesMeasure column for Y-axis (e.g., "FLIP_TOKEN").
format_stringNo
category_columnYesDimension column for X-axis (e.g., "MARKET_NAME").
show_data_labelsNo
value_aggregationYesSUM, COUNT, AVG, etc.
dataset_identifierYesThe dataset identifier.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It says only 'from simple parameters' and never discloses that this is a mutating operation that adds a visual to an existing sheet, nor any permission or side-effect implications.

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?

A single short sentence is front-loaded and not padded, but the phrase 'from simple parameters' is vague filler rather than useful information. It is concise but under-informative.

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?

With 10 parameters (7 required), an output schema, and no annotations, the description should clarify the mutation semantics and the relationship between analysis_id and sheet_id. Instead it leaves the agent to derive all of this from the schema alone.

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 coverage is 80%, so the schema already documents most parameters (analysis_id, sheet_id, category/value columns, aggregation). The description adds nothing beyond the schema, so the baseline of 3 applies.

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 verb and resource (create a bar chart), which is clear on its own. However, it offers no differentiation from the many sibling chart/visual creators like create_line_chart, create_pie_chart, create_combo_chart, and add_visual.

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?

There is no guidance on when to choose a bar chart over a line, pie, or combo chart, nor any mention of prerequisites such as the target analysis/sheet needing to exist. The agent must infer usage entirely.

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