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interview-prep-mcp

interview-prep-mcp

by shenmali
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

submit_practice_answer_tool

Submit a practice answer and receive an evaluation with score, strengths, gaps, and a suggestion for improvement.

Instructions

Submit an answer; returns evaluation (score + strengths + gaps + suggestion).

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": {
      "question_id": "<question_id>",
      "answer_text": "<answer_text>"
    },
    "name": "submit_practice_answer_tool"
  }
}

Input Schema

NameRequiredDescriptionDefault
question_idYes
answer_textYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are given, and the description provides minimal behavioral context. It does not disclose idempotency, side effects (e.g., resubmission), or authentication requirements.

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, front-loaded sentence with no fluff. Every word earns its place.

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

Completeness3/5

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

Given the presence of an output schema (not shown), the description might be adequate for a simple submission tool. However, with no annotations and zero parameter descriptions, it feels incomplete.

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

Parameters2/5

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

Schema description coverage is 0%, and the tool description adds no semantic detail beyond parameter names. The meaning is partially inferred but lacks constraints (e.g., allowed question IDs, answer format).

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 clearly states the tool's action (submit an answer) and outcome (returns evaluation with score, strengths, gaps, suggestion). It is specific but does not explicitly differentiate from sibling tools.

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?

No usage guidelines are provided. The description does not indicate when to use this tool versus alternatives (e.g., analyze_weak_areas_tool) or any prerequisites.

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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