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Glama

PeopleSearch.im

by im.peoplesearch

Reveal a person

reveal_profile
Idempotent

Unlock ONE person from a people_search result. Pass the token from that result. Spends 1 credit and returns the full profile: real name, current title and company, location and LinkedIn URL. Set include_email to true to also look up their verified professional (work) email in the same call, which spends 1 more credit that is refunded if no email is found. Revealing the same person again is free (idempotent). The email is looked up live and may take a moment: if it returns emailStatus 'searching', call reveal_profile again with the same token (no extra charge) to collect it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokenYesThe opaque `token` of a person returned by people_search.
include_emailNoAlso fetch the person's verified professional email (a second credit, refunded if none is found). Default false.

Schema Changelog

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

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

The description goes well beyond annotations by disclosing credit costs, the refund policy for email lookups, idempotent re-reveal behavior, live email latency, and the emailStatus 'searching' retry protocol. This is rich, actionable behavioral context with no contradiction to the annotations.

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 sentences, front-loaded with the core purpose, and every sentence adds necessary operational detail. There is no redundant restatement of the schema or annotations.

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?

Even without an output schema, the description lists the returned profile fields, covers the optional email path, credit impact, idempotency, and retry behavior. Given the two-parameter schema and the people_search provenance, nothing critical is missing for correct invocation.

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

Parameters5/5

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

Schema coverage is 100%, but the description adds essential semantics: where the token comes from, that include_email is processed in the same call, the extra refundable credit, and how to handle the 'searching' email status. These details are not inferable from the schema alone.

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 ('Unlock') and resource ('ONE person') while explicitly tying the input to a people_search result pool. This clearly distinguishes it from sibling tools like people_search, find_people, or fetch_email.

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?

Clear context is given: use it after a people_search returns a token, and set include_email when a verified email is also wanted. It does not explicitly name alternatives or say when not to use this tool, but the prerequisite is unambiguous enough for an agent.

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