ChartAnt

KPI cards

generate_kpi_card

Read-only

Draw 1 to 4 KPI cards as one image: each a big number with its label, optional change since the last period (green when good, red when bad) and an optional sparkline of recent values. For report emails, Slack updates and dashboards in documents.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "items": "<items>"
    },
    "name": "generate_kpi_card"
  }
}

Input Schema

Name	Required	Description
`items`	Yes
`title`	No	Heading above the cards, e.g. 'This week'.
`brandTheme`	No	Name of a brand theme saved on the user's account (their colours and footer), only when the user asks for their theme. Or "colorblind" for colours that people with colour-vision deficiency can tell apart (anyone can use it).

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 14, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. Beyond that, the description adds real behavioral context: the output is a single composed image, cards are capped at 1-4, and delta colouring is value-semantic (green when good, red when bad) rather than fixed. It stops short of saying how the image is returned (URL vs attachment) or how colours resolve when goodWhen='down'.

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?

Two sentences, zero filler, and the core capability plus card composition is front-loaded before the use-case sentence. Every clause carries information an agent can act on.

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

Completeness4/5

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

With a read-only annotation, three parameters and no output schema, the description does enough: it explains what the image contains and the item limits. The remaining gap is the shape of the returned artifact, which the absent output schema means the description would need to cover for full completeness.

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 coverage is 67%, so the baseline is 3, but the description adds semantics the schema does not: it ties 'change since the last period' to the delta field and explains the good/bad colour logic that drives goodWhen. The sparkline phrase maps trend to 'recent values', though unit, prefix, caption and deltaMode are left entirely to the 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 gives a concrete verb and resource ('Draw 1 to 4 KPI cards as one image') and even decomposes what a card contains: label, big number, delta, sparkline. That is far more specific than the name alone, but it never explicitly contrasts itself with the many chart-generating siblings (e.g. gauge, bullet, column), so an agent must infer that a card is not a chart.

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?

'For report emails, Slack updates and dashboards in documents' indicates the contexts where the output is useful, which is genuine implied guidance. However, it never says when to pick KPI cards over a gauge or bullet chart, nor any prerequisite or exclusion, leaving the alternative selection to inference.

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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