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AiAgentKarl

mcp-interactive-ui-server

create_dashboard

Generate a dashboard layout with configurable widgets (chart, stat_card, table, progress_bar, metric, list, markdown) and grid settings. Supports auto-refresh for real-time data.

Instructions

Generiert ein Dashboard-Layout mit verschiedenen Widget-Typen.

Erstellt eine strukturierte Dashboard-Definition mit konfigurierbarem Grid-Layout, die MCP-Clients als interaktives Dashboard rendern können.

Unterstützte Widget-Typen: chart, stat_card, table, progress_bar, metric, list, markdown.

Jedes Widget braucht mindestens: {"type": "stat_card", "title": "Users", "value": "1234"}

Args: title: Dashboard-Titel widgets: Liste von Widget-Definitionen (dicts mit type, title, etc.) description: Optionale Dashboard-Beschreibung columns: Anzahl Grid-Spalten (1-6) refresh_interval: Auto-Refresh in Sekunden (0 = kein Refresh)

Returns: JSON-String mit dem Dashboard-Schema

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYes
widgetsYes
descriptionNo
columnsNo
refresh_intervalNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries full burden. It states the output (JSON string with dashboard schema) and widget requirements, but does not explicitly confirm whether the tool has side effects (e.g., persistence) or is purely generative. The verb 'erstellt' is ambiguous, though the return format suggests no side effects.

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 well-structured with clear sections (supported types, example, args) and is informative without being overly verbose. Minor redundancy could be trimmed, but it remains concise and front-loaded.

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?

Overall, the description covers the tool's purpose, parameters, return type, and usage context adequately for an AI agent. It could be improved by clarifying the precise output schema format or persistence behavior, but it is sufficient given the tool's complexity.

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

Parameters5/5

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

The description adds significant value beyond the input schema, including constraints (columns 1-6), meaning of refresh_interval (seconds with 0 = no refresh), and detailed explanation of widgets with supported types and example structure. This compensates for the schema's minimal metadata.

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 it generates a dashboard layout with configurable grid layout and widget types. It lists supported widget types and provides an example, which distinguishes it from sibling tools like create_chart or create_table that serve different purposes.

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 description implies usage for creating interactive dashboards but does not explicitly compare to siblings or provide when-to-use/alternatives guidance. The context is implied by the tool's name and description, but no exclusions or prerequisites are mentioned.

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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