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Glama

RooQuiz

get_examinee

Read-only

View the full detail of one examinee (a.k.a. respondent) in the current team by its examineeId (the business ID shown in list_examinees, e.g. AB1234567890), including customData. Sensitive auth fields are never returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
examineeIdYesThe examinee business ID (e.g. AB1234567890), as shown in list_examinees

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoMasked name (J*n)
emailNoMasked email (j***g@example.com); never pass it back as an argument
avatarNoUploaded avatar as { id, url }
statusNoAccount status
tenantNoTeam (tenant) the respondent belongs to
createdAtNoISO datetime of first sign-up
updatedAtNoISO datetime of the last change
customDataNoTeam-defined custom fields; phone-typed values come back masked
examineeIdNoBusiness ID of the respondent (e.g. AB1234567890) — use it to address them
avatarPresetNoPreset avatar key, when no image was uploaded
emailVerifiedNoWhether the email has been verified

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover readOnlyHint and destructiveHint, and the description adds useful behavioral details: scoping to the current team and explicitly stating that sensitive auth fields are never returned.

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 two concise, front-loaded sentences with no filler. It covers the key facts in order: action, scope, identifier, included data, and an important security guarantee.

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?

Given one well-documented parameter, read-only annotations, and an output schema being present, the description is complete enough for an agent to correctly select and call the tool. Team scope, ID source, included data, and excluded fields are all stated.

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 examineeId as the business ID shown in list_examinees. The description repeats the same example and adds little beyond what the parameter schema already provides.

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 states a specific verb ('View the full detail of one examinee') and a specific resource, clearly distinguishing a full single-record lookup from list_examinees. It also mentions the key identifier and that customData is included.

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 clearly sets the context: use this on an examinee in the current team, and find the examineeId from list_examinees. It does not explicitly name alternatives or exclusions, but the intended read-only retrieval flow is 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

A4.1/5.0
Disambiguation4/5

Most tools pair a distinct resource with a distinct verb, and the descriptions do a good job of separating related concepts like leads, records, examinees, and bookings. The only real ambiguity is between list_records (submission records, also called leads) and list_leads (CRM leads), plus a mild overlap between update_form and update_form_settings, but careful reading resolves both.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern, using standard verbs like get_, list_, create_, update_, delete_, add_, insert_, move_, and set_. Minor stylistic variation such as add_question vs. insert_question is still predictable and does not hurt usability.

Tool Count2/5

48 tools is a very heavy surface for an MCP server. While each tool appears purposeful, the server spans forms, questions, translations, analytics, leads, bookings, examinees, media, and team administration, making it feel like a full platform API rather than a focused server. Most agents will only ever need a subset of these tools.

Completeness4/5

The core quiz lifecycle is well covered: form creation/editing/deletion/restore/duplicate/translation, question CRUD/move, delivery settings, statistics/funnels, lead CRM, bookings, examinees, media upload, and tenant basics. The main gaps are minor — no member list/remove/role management beyond invite, no media library listing/deletion, and no bulk export of records — but these do not create dead ends in the primary quiz/lead/booking workflows.

Resources