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interview-prep-mcp

interview-prep-mcp

by shenmali
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

start_interview_prep_tool

Create a new interview prep session with company and role details. Returns a unique session ID and metadata to track progress.

Instructions

Create a new interview prep session and return its id + metadata.

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": {
      "company": "<company>",
      "role": "<role>"
    },
    "name": "start_interview_prep_tool"
  }
}

Input Schema

NameRequiredDescriptionDefault
companyYes
roleYes
job_idNo
cv_idNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations, the description must carry the full burden. It mentions creation and return of id+metadata but does not disclose side effects, authorization requirements, rate limits, or whether it modifies persistent state. This is insufficient for a mutation tool.

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 a single sentence that directly states the action and outcome. It is appropriately front-loaded and concise, though it could benefit from a brief elaboration on session scope.

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

Completeness2/5

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

Given the tool's complexity (4 parameters, no annotations), the description is too brief. It does not clarify how session creation relates to other tools (e.g., generating questions) or what metadata is returned. The output schema exists but is not referenced.

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%, so the description should explain parameters. It does not describe the meaning of company, role, job_id, or cv_id beyond their names. The optional parameters are not explained, leaving ambiguity about their purpose.

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 it creates an interview prep session and returns id + metadata. The verb and resource are specific, and it is distinguishable from sibling tools which perform different actions (e.g., generate_questions, analyze_weak_areas). However, it does not elaborate on what constitutes a session.

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 guidance is provided on when to use this tool versus alternatives, such as set_active_cv or list_interviews. There are no prerequisites, exclusions, or context for its use.

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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