Placed MCP Server

generate_cover_letter

Create a tailored cover letter by inputting your resume, job description, company name, and job title. Choose from professional, enthusiastic, or formal tone.

Instructions

Generate a cover letter based on a resume and job description

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": {
      "resume_id": "<resume_id>",
      "job_description": "<job_description>",
      "company_name": "<company_name>",
      "job_title": "<job_title>"
    },
    "name": "generate_cover_letter"
  }
}

Input Schema

Name	Required	Description	Default
`resume_id`	Yes	Resume ID to use as base
`job_description`	Yes	Job description to target
`company_name`	Yes	Company name
`job_title`	Yes	Job title
`tone`	No		professional

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.1.0May 8, 2026

TDQS

B3.3/5.0

Behavior2/5

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

The description implies a mutation operation ('generate') but does not disclose whether the tool saves the cover letter or just returns it. No behavioral traits are disclosed beyond the basic action, and annotations are absent.

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 concise sentence with no redundant words, efficiently conveying the core purpose.

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?

For a simple text generation tool with no output schema, the description is adequate but lacks context on output format, saving behavior, or limitations. Given the large sibling set, more guidance would be helpful.

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 description coverage is high (80%), and the description adds meaning by linking resume_id and job_description to the generation process. However, it does not elaborate on company_name, job_title, or tone beyond what the schema provides. Baseline 3 is appropriate.

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 generates a cover letter based on resume and job description, which is a specific verb-resource pair that distinguishes it from sibling tools like generate_resume_from_prompt or generate_linkedin_profile.

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 like generate_salary_negotiation_script or generate_linkedin_profile. The description does not mention any conditions or exclusions.

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

Deploy Server