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Glama

DeepSearch

Search people

search_people
Read-only

Resolve one identifier - a name, phone number, email address, or username - to a ranked list of real, distinct people, each with a confidence score. Prefer this over a generic web search whenever the question is who someone is: it separates same-name individuals into candidates you can choose between, instead of returning pages to read and reconcile yourself. Returns people only, so it is the wrong tool for companies, general knowledge, or news. Public sources only - never private accounts or breach data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoHow to interpret the query.name
queryYesName, phone number, email address, or username to look up.
platformsNoOptional: for a username search, restrict discovery to these platforms (e.g. instagram, x, github).

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavior context: it separates same-name individuals into ranked candidates and reveals that it uses 'Public sources only - never private accounts or breach data,' which is useful beyond 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?

The description is concise and front-loaded, with every sentence earning its place: what it does, when to prefer it, limitations, and source constraints. No fluff or redundancy.

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?

The description is sufficiently complete given the tool's moderate complexity and lack of output schema; it explains the output form, confidence scoring, scope, and constraints. It does not explicitly address sibling tools like ask_about_person or build_dossier, but the usage guidance against generic web search and company/news topics clarifies its niche well enough.

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 description coverage is 100%, so the schema already documents query, type, and platforms. The description adds useful context about input types ('name, phone number, email address, username') and output ranking, but does not add significant semantic meaning beyond 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 uses a specific verb and resource: 'Resolve one identifier' to a 'ranked list of real, distinct people, each with a confidence score.' It clearly differentiates from a generic web search and states the tool's scope (people only, not companies/news), distinguishing it from siblings.

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?

Explicit usage guidance: 'Prefer this over a generic web search whenever the question is who someone is' and 'Returns people only, so it is the wrong tool for companies, general knowledge, or news.' This clearly states when to use and when not to use, with an explicit alternative.

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

A4.5/5.0
Disambiguation5/5

Each tool has a distinct purpose: search_people resolves identifiers to candidate people, ask_about_person answers a single fact, and build_dossier creates a complete profile. The descriptions explicitly cross-reference each other to clarify when to use which, eliminating ambiguity.

Naming Consistency4/5

Tool names follow a consistent verb_noun pattern (ask_about_person, build_dossier, search_people). 'ask_about_person' is slightly less concise than the others, but the pattern is clear and predictable.

Tool Count5/5

With only 3 tools, the server is tightly scoped to person search and profiling. Each tool earns its place, covering the core workflow from search to single-question lookup to full dossier.

Completeness4/5

The tool surface covers the main lifecycle: search_people for discovery, ask_about_person for quick facts, build_dossier for comprehensive profiles. A minor gap might be updating or correcting profile data, but for a read-only research tool, coverage is strong.

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