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Ninova MCP

Ninova MCP

by hikmedit
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Get Dashboard

get_dashboard

Summarizes your Ninova dashboard, providing a quick overview of courses, recent announcements, assignments, and messages.

Instructions

Read the Ninova dashboard and summarize courses, recent announcements, assignments, and messages.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_dashboard"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.5

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description must convey behavioral traits. It states 'Read' indicating read-only, but does not disclose any side effects, authentication needs, or data aggregation details. The presence of an output schema helps, but more context would improve transparency.

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?

Single sentence, front-loaded with key action 'Read', and covers all major data types without extraneous words. Excellent conciseness.

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?

Given zero parameters, an output schema, and a set of sibling tools that cover specific aspects, the description is fairly complete. It could mention that it provides an aggregated summary, but overall it provides sufficient context.

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?

There are no parameters, and schema description coverage is 100%. The baseline is 3 because the description adds no parameter information, which is fine since there are none.

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?

Description uses specific verb 'Read' and resource 'Ninova dashboard', and lists the data types summarized (courses, announcements, assignments, messages). This clearly distinguishes it from sibling tools like get_dashboard_announcements which are more focused.

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

Usage Guidelines4/5

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

The description implicitly suggests using this for a general dashboard overview, but does not explicitly state when not to use it or mention alternatives. Given the clear sibling differentiation, it is still effective.

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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