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Register candidates for interview

register_users_for_interview
Destructive

[Interviews] Register users/candidates for a specific interview and return their personal interview links.

Registers (or updates) one or more candidate profiles for an interview and returns a one-time interview URL for each. Accepts a Supabase user JWT (merchant/admin) or the service key (merchant_id then required).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
usersYesCandidates to register for the interview. Each gets a one-time interview URL.
is_testNoWhen true (or the string "true"), mints a test token that can take a draft/unpublished interview and flags the result as a test. For a DRAFT interview it also recompiles the definition (interview_recalc_definition) first, so the test session includes the current questions/welcome. This makes it a single-call "trigger interview test".
hide_menuNoWhen true (or the string "true"), the interview UI hides its menu (view_hm).
send_emailNoWhether to send an invitation email to each registered candidate.
hide_iframeNoWhen true (or the string "true"), the interview UI hides its iframe chrome (view_hi).
merchant_idNoMerchant id. Required when authenticating with the service key; for user tokens it is optional and only honored for admin / sub-merchant accounts.
interview_idYesInterview definition (interview_def_set) or position (position_def_set) id to register users for.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYesThe input users, each annotated with its registration result and (on success) interview URL.

TDQS

A4.2/5.0
Behavior4/5

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

The description adds useful behavioral context beyond annotations: it discloses that the operation registers or updates profiles, returns one-time interview URLs, and has different auth requirements. While destructiveHint is true, the description doesn't spell out destructive side effects, but it does not contradict 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?

The description is two tight sentences with no filler. It front-loads the core operation in the first sentence and adds auth nuance in the second, making it easy for an agent to quickly grasp the tool's purpose.

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?

Given the rich input schema, output schema, and annotations, the description covers the essential operation, return value, and auth requirements. It is complete enough for correct invocation, though it could be slightly stronger by explicitly stating what the destructive hint implies for existing candidate registrations.

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 all 7 parameters thoroughly. The description reinforces the merchant_id/service-key relationship and the per-user URL return, but does not add significant meaning beyond what the schema 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 and resource: 'Register users/candidates for a specific interview' and returns their personal interview links. It clearly distinguishes this from sibling tools by emphasizing the registration/update of candidate profiles and the one-time URL output.

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?

The description gives clear context for when to use the tool: when candidates need to be registered or updated for an interview and per-candidate interview links are needed. It also provides authentication guidance (user JWT vs service key with merchant_id), but does not explicitly name alternatives or when-not-to-use conditions.

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

A3.6/5.0
Disambiguation4/5

Most tools target distinct resources and actions, with clear category prefixes like [Interviews], [Results], and [Admin]. A few pairs could be confused—create_interview vs. create_interview_from_questions and update_interview vs. set_interview_state—but the descriptions do enough to separate them.

Naming Consistency4/5

The overwhelming majority follow a consistent verb_noun pattern: create_*, get_*, list_*, update_*, generate_*. The main deviation is jobmojito_configuration, which is a noun phrase rather than an action verb, and a few longer names like request_another_interview_attempt break the clean pattern slightly.

Tool Count2/5

With 29 tools, this server is above the 25+ threshold and places a significant navigation burden on an agent. The tools are organized into coherent domains, but several admin/merchant and results tools could likely be consolidated.

Completeness3/5

The core interview lifecycle is well covered: create, read, update, list, state changes, result retrieval, and report generation. However, there are notable gaps such as no delete operations for interviews or catalogue directories, no candidate management beyond listing/registration, and no explicit result-decision tool.