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Hassan220022

harvestapi-mcp

by Hassan220022

harvest_get_profile

Fetches a LinkedIn profile using a URL, public identifier, or profile ID, with optional email discovery and About section scraping.

Instructions

Get LinkedIn profile — requires at least one of url, publicIdentifier, profileId. Flags: main, findEmail, skipSmtp, includeAboutProfile.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoURL of the LinkedIn profile, e.g. https://www.linkedin.com/in/williamhgates
mainNoSet to true to return only main profile sections (fewer credits)
skipSmtpNoSet to true together with findEmail to skip SMTP verification (fewer credits)
findEmailNoSet to true to find and validate the profile email (more credits). Performs SMTP checks; catch-all domains marked risky
profileIdNoID of the LinkedIn profile
publicIdentifierNoPublic identifier (last part of profile URL), e.g. williamhgates
includeAboutProfileNoSet to true to scrape the About this profile popup
Behavior2/5

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

With no annotations, the description provides no detail on side effects, authentication, rate limits, or credit implications of flags like findEmail. It merely lists flags without explaining their behavioral consequences, leaving the agent underinformed.

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 sentence with a compact flag list, front-loading the action and avoiding redundancy. Every word serves a 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?

The description covers the core action and lists flags but does not describe the return structure, error conditions, or credit costs. Since there is no output schema and no annotations, the agent is left without expectations for what the tool returns.

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

Parameters4/5

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

The schema already provides thorough descriptions for all 7 parameters, so the description adds little per-parameter meaning. However, the one-of requirement for url, publicIdentifier, or profileId is a valuable cross-parameter constraint not captured in the schema.

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 retrieves a LinkedIn profile using a specific verb and resource. It distinguishes from sibling tools like harvest_search_profiles by indicating direct retrieval given an identifier.

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?

It specifies a prerequisite (one of url, publicIdentifier, profileId) but does not explicitly contrast with search_profiles or other alternatives. Usage is implied by the tool's purpose rather than explicitly guided.

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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