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kula-ai

@kula-ai/mcp-server

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by kula-ai

list_scorecard_submissions

Retrieve scorecards for a given application, with optional filters for activity type (interview, assessment, review) and status (draft, submitted). Supports pagination and date range filtering.

Instructions

List scorecards for a specific application. Each scorecard may be linked to an interview, assessment, or review — use the type filter to narrow by activity type.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
application_idYesApplication ID
statusNoComma-separated statuses to filter by: draft, submitted
typeNoComma-separated activity types to filter by: interview, assessment, review
pageNoPage number
limitNoItems per page
sort_byNoField to sort by (default: created_at)
sort_orderNoSort direction (default: desc)
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)
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 correctly implies a read operation but does not disclose details like pagination behavior, response format, or authentication needs. The description is adequate but lacks depth.

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 a single, well-structured sentence that front-loads the main action and includes a key hint about filtering. It is concise and every word earns its place.

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?

With 11 parameters and no output schema, the description is sparse. It does not explain the response format or pagination. Some guidance on what the list returns would improve completeness, but the schema covers parameters well.

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% with descriptions for all 11 parameters. The description adds no additional meaning beyond the schema (only mentions the type filter). Baseline is 3 per guidelines.

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 tool lists scorecards for a specific application (verb + resource + scope). It distinguishes from siblings like list_scorecard_templates by specifying the link to activities and a type filter.

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 (listing scorecards for an application) and mentions the type filter to narrow by activity type. However, it does not explicitly state when not to use or suggest alternatives, so it falls short of a 5.

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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