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nulab

Backlog MCP Server

get_pull_requests_count

Count pull requests in a Backlog repo using filters like status, assignee, or issue. Get the total number of PRs meeting your criteria.

Instructions

Returns count of pull requests for a repository

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdNoThe numeric ID of the project (e.g., 12345)
projectKeyNoThe key of the project (e.g., 'PROJECT')
repoIdNoRepository ID
repoNameNoRepository name
statusIdNoStatus IDs
assigneeIdNoAssignee user IDs
issueIdNoIssue IDs
createdUserIdNoCreated user IDs
organizationNoOptional organization name. Use list_organizations to inspect available organizations.
Behavior2/5

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

No annotations are provided, and the description does not disclose any behavioral traits beyond the basic operation. It does not mention whether the tool is read-only, how it handles conflicting parameters, or any rate limits or side effects. The minimal description fails to carry the burden of transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise at one sentence, but it is under-specified for the tool's complexity. Every word is functional, but additional context about filtering or repository identification would be valuable without losing conciseness.

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?

Given 9 optional parameters and no output schema, the description is incomplete. It does not explain how to construct a valid request (e.g., which parameters are needed for repository identification) or what the returned count represents when filters are applied. The tool's complexity demands more contextual information.

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 baseline is 3. The description itself adds no additional meaning to the 9 parameters beyond what the schema already provides. The description is too brief to enhance parameter understanding, but since the schema is self-contained, this is acceptable.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the function: returns a count of pull requests for a repository. It is not a tautology and the name reinforces the purpose. However, it does not explicitly differentiate from get_pull_requests which returns a list, but the noun 'count' implicitly suggests this distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like get_pull_requests. There is no information on which repository parameters are required or how to specify filters. The agent is left to infer usage from the schema and context.

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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