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kula-ai

@kula-ai/mcp-server

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by kula-ai

list_applications

List job applications with filters for status, job ID, stage, date range, and more. Retrieves application records from the recruiting system.

Instructions

List job applications. Only use when the user explicitly asks about applications.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number
limitNoItems per page
job_idNoFilter by job ID
statusNoComma-separated application statuses to filter by (active, hired, rejected, duplicate)
stage_idsNoComma-separated stage IDs to filter by
credited_to_user_idsNoComma-separated user IDs to filter by credited user
sort_byNoField to sort by
sort_orderNoSort direction
created_afterNoFilter by created date (ISO 8601, inclusive lower bound)
created_beforeNoFilter by created date (ISO 8601, inclusive upper bound)
updated_afterNoFilter by updated date (ISO 8601, inclusive lower bound)
updated_beforeNoFilter by updated date (ISO 8601, inclusive upper bound)
Behavior2/5

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

No annotations provided, so description must cover behavioral traits. It only says 'List job applications' without mentioning pagination, permissions, or that it is read-only. The name implies listing, but safety or side effects are not disclosed.

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 concise sentences, front-loaded with purpose and usage condition. No wasted words.

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

Completeness2/5

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

With 12 parameters, no output schema, and many sibling list tools, the description is too minimal. It does not explain pagination, filtering, or return format, leaving the agent 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 100%, so description does not need to add param info. It adds no extra meaning beyond what is in the schema, meeting the baseline.

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 the verb 'List' and resource 'job applications', and adds a usage condition 'Only use when the user explicitly asks about applications', which distinguishes it from other tools.

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 ('only when user asks about applications'), but does not mention alternatives like 'get_application' for single applications or 'search_candidates' for broader queries.

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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