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kula-ai

@kula-ai/mcp-server

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by kula-ai

list_email_templates

Retrieve configured email and calendar-invite templates. Filter by name, channel, category, owner, or date range to find template IDs for interview creation.

Instructions

List email and calendar-invite templates configured for the account. Per-interview snapshots and system templates are excluded. Use this to discover interviewer_template_id and candidate_template_id for create_interview.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
limitNo
queryNoFilter by template name (case-insensitive substring)
channelNoFilter by delivery channel
categoriesNoComma-separated categories: adhoc, interview_coordination, interviewer_coordination, email_activity, application_submission, assessment, rejection, offer, self_schedule_invite, availability, survey
owner_idsNoComma-separated owner user IDs
sort_byNo
sort_orderNo
created_afterNo
created_beforeNo
updated_afterNo
updated_beforeNo
Behavior3/5

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

Discloses exclusion of per-interview snapshots and system templates. No annotations provided, so description carries full burden; but it lacks details on pagination, authorization, or rate limits.

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?

Two well-structured sentences. First states what the tool does, second gives a concrete use case. No redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 12 parameters, no output schema, and no annotations, the description covers purpose and a key usage scenario but lacks details on return structure, pagination defaults, and filter behavior. Adequate but with gaps.

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 coverage is 33% (4 of 12 params have descriptions). Description adds the use-case context (returning template IDs) but does not compensate for the many undocumented parameters like page, limit, date filters. Baseline 3 with partial compensation.

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?

Clear verb 'list' with specific resource 'email and calendar-invite templates', excludes snapshots/system templates, and explicitly tells agent to use it for discovering template IDs for create_interview. Distinguishes from siblings like get_email_template.

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?

Explicitly states when to use (discover template IDs for create_interview) and what is excluded. Does not explicitly mention alternatives, but the purpose is clear enough for an agent to infer.

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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