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Glama

PeopleSearch.im

by im.peoplesearch

Find a LinkedIn profile

find_linkedin_profile

Find the LinkedIn profile URL for a named person. Provide their first and last name; adding the company or domain sharply improves the match. Spends 2 credits, refunded if no confident match is found.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
last_nameYesThe person's last name.
first_nameYesThe person's first name.
company_or_domainNoOptional but recommended: the company name or domain they work at, to disambiguate common names.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

The description adds valuable behavioral context beyond the annotations by disclosing the credit cost and refund policy for unmatched results. No contradiction with annotations; readOnlyHint=false is consistent with spending credits.

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 three tightly written sentences: purpose first, then input guidance, then cost/refund behavior. Every sentence earns its place with no repetition or filler.

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

Completeness4/5

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

For a simple lookup tool with no output schema, the description covers inputs, expected output, and cost/refund behavior. It does not detail the exact URL format or what happens on a non-confident match, but it is sufficient for correct invocation.

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?

Schema coverage is 100%, so the schema already documents each parameter. The description adds extra value by emphasizing that company_or_domain sharply improves match success, which helps agents decide whether to populate an optional field.

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 the tool's purpose: finding the LinkedIn profile URL for a named person. It specifies a concrete verb, resource, and input requirement, but it does not explicitly differentiate itself from siblings like lookup_linkedin_profile or reveal_profile.

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?

It gives clear operational guidance: provide first and last name, and use company_or_domain to improve match quality. It does not explicitly state when to prefer this tool over alternative lookup tools, but the intended use case is reasonably clear.

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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TDQS

A4.2/5.0
Disambiguation4/5

Most tools have distinct purposes, but pairs like company_search/lookup_company and find_linkedin_profile/lookup_linkedin_profile could cause selection errors. The free-search versus paid-unlock flow (people_search/find_people/reveal_profile) is well-differentiated by detailed descriptions.

Naming Consistency3/5

Naming mixes verb_noun patterns (find_people, fetch_email) with noun_verb patterns (company_search, people_search), and uses overlapping verbs like find, lookup, search, and fetch. The pattern is readable but not consistently predictable.

Tool Count5/5

With 12 tools, the set is well-scoped for a people search and email enrichment service. Each tool covers a distinct operation, from free search to paid profile unlock, email verification, and credit checking, without unnecessary bloat.

Completeness4/5

The toolset covers the core lifecycle: free search, paid profile unlock, email fetch, verification, and reverse lookup. Minor gaps exist, such as not being able to fetch an email later for a profile unlocked via reveal_profile unless include_email is set initially, but agents can work around these.

Resources