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Ray0907

Git MCP Server

by Ray0907

list_issues

Retrieve and filter project issues by state, labels, assignee, author, or search terms to manage and track development tasks.

Instructions

List issues in a project with optional filters

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoYesRepository identifier (GitLab: "group/project" or ID, GitHub: "owner/repo")
stateNoFilter by state
labelsNoFilter by labels
searchNoSearch in title and description
assignee_idNoFilter by assignee ID
author_idNoFilter by author ID
sortNoSort field
directionNoSort direction
pageNoPage number (default: 1)
per_pageNoItems per page (default: 20, max: 100)
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions 'optional filters' but lacks critical behavioral details such as pagination behavior (implied by 'page' and 'per_page' parameters), rate limits, authentication needs, or what the output looks like (e.g., list format). This is inadequate for a tool with 10 parameters and no output schema.

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, efficient sentence that front-loads the core purpose ('List issues in a project') and adds a key detail ('with optional filters'). There is no wasted verbiage, making it appropriately concise and well-structured.

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 the complexity (10 parameters, no output schema, and no annotations), the description is insufficient. It doesn't address behavioral aspects like pagination, error handling, or output format, leaving significant gaps for an AI agent to understand how to use the tool effectively.

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%, providing detailed descriptions for all parameters. The description adds minimal value beyond the schema by mentioning 'optional filters', but doesn't explain parameter interactions or provide additional context. This meets the baseline of 3 when schema coverage is high.

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 verb ('List') and resource ('issues in a project'), making the purpose specific and understandable. However, it doesn't distinguish this tool from sibling tools like 'get_issue' or 'list_pull_requests', which would require explicit differentiation for a score of 5.

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 like 'get_issue' (for single issues) or 'search_code' (for code-related queries). It mentions 'optional filters' but doesn't specify contexts or exclusions, leaving usage unclear relative to siblings.

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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