CampusMind-AI

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end_voice_session

End a voice session to log a summary interaction and retrieve session statistics like duration, interaction count, and topics covered.

Instructions

Ends an active voice session, logs a summary interaction, and returns session statistics including duration, interaction count, and topics covered.

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": {
      "studentId": "<studentId>",
      "sessionId": "<sessionId>"
    },
    "name": "end_voice_session"
  }
}

Input Schema

Name	Required	Description	Default
`sessionId`	Yes	The voice session ID to end
`studentId`	Yes	The student ID ending the session

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jul 31, 2026

TDQS

A4/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the side effect of logging a summary interaction and the return of session statistics, which are behavioral traits. However, it does not mention error handling, state requirements (e.g., session must be active), or whether it is idempotent. Still, it provides substantive transparency beyond a bare 'Ends a session'.

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, well-structured sentence that front-loads the primary action and efficiently covers side effects and return values. Every clause adds value without redundancy or wasted words.

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?

The tool is relatively simple, and the description adequately covers the core action, side effect, and return values. Since there is no output schema, the explicit mention of returned statistics (duration, interaction count, topics covered) is useful. It lacks details about failure modes or preconditions, but those are not critical for basic usability.

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 100% with clear descriptions for both parameters ('The voice session ID to end' and 'The student ID ending the session'). The description adds no additional parameter-specific meaning, so a baseline score of 3 is appropriate when the schema already handles semantics effectively.

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 the tool ends an active voice session, with specific verb 'Ends' and resource 'voice session'. It also distinguishes itself from siblings like 'start_voice_session' by describing the ending and additional logging/statistics behavior.

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 intended usage is implied (when you want to end a voice session), but there is no explicit guidance on when to use this tool vs alternatives, prerequisites like having an active session, or exclusions. No alternatives are mentioned, so it lacks direct usage direction.

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