Skip to main content
Glama
jcnh74

linkedin-profile-manager-mcp

by jcnh74

Generate headline variants

generate_headline_variants

Generate multiple LinkedIn headline options for your target role. Supports roles like senior full-stack engineer, agentic AI systems engineer, and more, up to 8 variants.

Instructions

[risk: draft-only] Generates draft text locally. Nothing is sent to LinkedIn. Generate LinkedIn headline options (max 220 chars) for a target role.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
targetRoleYes
Behavior4/5

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

Despite no annotations, the description discloses key behavioral traits: it is draft-only and nothing is sent to LinkedIn. This clarifies non-destructive behavior, though auth or rate limits are not mentioned.

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 two sentences, front-loading the risk and purpose. Every sentence adds value with no redundancy.

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?

The description omits the output format (e.g., list of strings) and does not mention the count parameter. Given no output schema, this gap reduces completeness for an agent.

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 coverage is 0%. The description does not explain the 'count' or 'targetRole' parameters, despite the schema providing defaults, enums, and constraints. The agent lacks guidance on parameter usage.

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 it generates LinkedIn headline options with a character limit for a target role. This distinguishes it from sibling tools like rewrite_about_section or keyword_gap_analysis.

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 explicitly notes it is draft-only and local, indicating safe use for drafting. However, it does not specify when not to use it or mention alternatives.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/jcnh74/linkedin-profile-manager-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server