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kula-ai

@kula-ai/mcp-server

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by kula-ai

update_interview

Update an existing interview's start time, duration, interviewers, location, and more. Only supplied fields are modified; cancelled interviews cannot be updated.

Instructions

Update an existing interview. All fields are optional — only the supplied fields are modified. Immutable fields (cannot be changed after creation): organizer_id, application_id, job_id, stage_id, candidate_id, stage_activity_id, scorecard_template_id. Cancelled interviews cannot be updated (returns 422 err_interview_cancelled).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesInterview ID
start_timeNoNew start_time (ISO 8601, on 15-min boundary, zero seconds)
duration_minutesNoMultiple of 15, 15..1440
timezoneNoIANA timezone (e.g., America/Los_Angeles)
kindNoInterview type: one_on_one | panel
locationNoLocation: onsite | phone | zoom | google_meet | microsoft_teams | hackerrank
interviewer_idsNo
office_idNoRequired when location=onsite
host_idNoRequired when location=zoom; must be in interviewer_ids
hackerrank_template_idNoRequired when location=hackerrank
nameNo
calendar_event_visibilityNoVisibility: default | private
ai_note_taker_enabledNo
ai_scorecard_assist_enabledNo
interviewer_template_idNoFrom list_email_templates
candidate_template_idNoFrom list_email_templates
Behavior3/5

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

No annotations are provided, so the description carries full burden. It discloses optional fields, immutable fields, and cancellation error. However, it lacks details on authorization, rate limits, or idempotency, which are important for a mutation tool.

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 main action, no redundant words. Every sentence adds distinct information: core function, optionality, immutability, and error condition.

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 16 parameters, no output schema, and no annotations, the description covers essential behavioral context (optional fields, immutable fields, cancellation constraint). It does not describe return values, but that is acceptable without an output schema.

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 75%, and the description adds value beyond schema by stating that all fields are optional and only supplied fields are modified. It also lists immutable fields, which aids parameter understanding.

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 clearly states 'Update an existing interview' with specific verb-resource. It distinguishes from siblings like create_interview and cancel_interview by mentioning constraints such as immutable fields and cancelled interview restrictions.

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 provides clear context for when to use (any update) and when not to (cancelled interviews, immutable fields). It does not explicitly mention alternatives among siblings, but the constraints implicitly guide usage.

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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