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scrape_profile

Read-onlyIdempotent

Fetch a complete LinkedIn profile (name, headline, company, experience, skills…). Pass a LinkedIn URL, vanity name, internal member ID, or Sales Navigator lead URL. Uses SalesNav API when available for richer data. Use to read one person in depth (experience, skills, company); costly, one LinkedIn call per profile. For a list of people use scrape_search; to just check the relationship use get_invitation_status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
account_idYesReach id of the LinkedIn account to act on, from list_accounts.
linkedin_id_or_urlYesLinkedIn profile URL, vanity name, Sales Navigator URL, or internal member ID.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobNoCurrent job title.
degreeNoNetwork degree: 1, 2, or 3.
skillsNo
companyNoCurrent company name.
pictureNoProfile picture URL.
summaryNo
headlineNo
industryNo
lastnameNo
locationNo
firstnameNo
full_nameNoFull name as returned by LinkedIn (standard search only).
languagesNo
company_idNoLinkedIn company ID.
is_premiumNo
connectionsNo
linkedin_idNoProfile ID (fsd_profile or ts_profile suffix).
profile_urlNoPublic LinkedIn profile URL.
company_logoNo
company_typeNo
year_companyNoTenure at current company (years).
is_opentoworkNo
month_companyNoTenure at current company (months).
year_positionNoTenure at current position (years).
month_positionNoTenure at current position (months).
company_websiteNo
is_open_profileNo
job_descriptionNo
company_industryNo
company_linkedinNoLinkedIn company page URL.
company_locationNo
linkedin_plain_idNoNumeric member ID (objectUrn suffix).
linkedin_public_idNoVanity URL slug (/in/<slug>).
salesnavigator_urlNoSales Navigator profile URL (SalesNav searches only).
startyear_positionNo
company_descriptionNo
company_specialtiesNo
startmonth_positionNo
company_year_foundedNo
company_employee_countNo
company_employee_rangeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds genuinely new behavioral context: the per-call cost and the fact that SalesNav API is used opportunistically when available for richer data. It stops short of describing failure modes or rate-limit behavior, so not a 5.

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?

Four tight sentences, front-loaded with the outcome and input flexibility before the cost warning and the sibling routing. No filler, and the most decision-relevant facts come first.

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

Completeness5/5

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

With an output schema present, the description needn't explain return values, and it covers everything else an agent needs: accepted identifier forms, cost, data-source behavior, and sibling selection. Nothing material is missing for a two-parameter read tool.

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 coverage is 100% and both parameters are fully documented in the schema, so the schema carries the load. The description restates the accepted identifier formats (URL, vanity name, member ID, SalesNav lead URL), which largely duplicates the schema rather than extending it.

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?

States a specific verb (Fetch) and resource (complete LinkedIn profile) and enumerates what is returned (name, headline, company, experience, skills). It explicitly distinguishes itself from scrape_search and get_invitation_status, so an agent can route without opening sibling schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit when-to-use ('read one person in depth'), the cost tradeoff ('costly, one LinkedIn call per profile'), and names two alternatives with the conditions that select them (scrape_search for lists, get_invitation_status for relationship checks).

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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