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zenhub-mcp

zenhub-mcp

by derekbar90
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

zenhub_search_issues

Search and filter issues in a pipeline by title, labels, or assignees.

Instructions

Search and filter issues within a specific pipeline by title, labels, or assignees

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "pipeline_id": "<pipeline_id>"
    },
    "name": "zenhub_search_issues"
  }
}

Input Schema

NameRequiredDescriptionDefault
pipeline_idYesPipeline ID to search in. Use zenhub_get_workspace_overview to get pipeline IDs.
queryNoSearch query for title, user (github login name), content
filtersNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.8

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations provided, the description must fully disclose behavior. It lacks information about return format, pagination, performance constraints, or any side effects. Only the basic function is stated, which is insufficient for a search 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?

The description is a single, concise sentence that communicates the core functionality without extraneous content. Every word contributes to clarity.

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?

The description omits details about output format, result limits, sorting, and error cases. Given the nested filters parameter and absence of an output schema, the description is incomplete for an AI agent to reliably handle tool invocation.

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 67%, and the description lists the filtering dimensions (title, labels, assignees) already present in the schema. It adds no extra meaning beyond what the parameter descriptions already provide, so a baseline score of 3 is appropriate.

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 'Search and filter' and the resource 'issues within a specific pipeline', with specific criteria 'title, labels, or assignees'. This distinguishes it from sibling tools like zenhub_search_issues_in_repository, which searches within a repository rather than a pipeline.

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?

The description provides no guidance on when to use this tool versus alternatives such as zenhub_get_workspace_issues or zenhub_search_issues_in_repository. It does not indicate prerequisites or exclusions, leaving the agent to infer usage 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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