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Sunwood-ai-labs

GitHub Kanban MCP Server

list_issues

Retrieve issues from a GitHub Kanban board, with optional filtering by state (open, closed, all) and labels to streamline task management.

Instructions

カンバンボードのissue一覧を取得します

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoGitリポジトリの絶対パス
stateNoissueの状態
labelsNoフィルタリングするラベル

Implementation Reference

  • The main handler function that executes the 'list_issues' tool logic. It retrieves repo info, constructs a gh CLI command with optional state/labels filters, and returns the JSON output.
    export async function handleListIssues(args: IssueArgs): Promise<ToolResponse> {
      const { owner, repo } = await getRepoInfo(args);
      const stateFlag = args.state ? `--state ${args.state}` : '';
      const labelsFlag = args.labels?.length ? `--label ${args.labels.join(',')}` : '';
      
      const { stdout } = await execAsync(
        `gh issue list --repo ${owner}/${repo} ${stateFlag} ${labelsFlag} --json number,title,state,labels,assignees,createdAt,updatedAt`
      );
    
      return {
        content: [
          {
            type: 'text',
            text: stdout,
          },
        ],
      };
    }
  • JSON Schema for list_issues input validation. Defines optional path (string), state (enum: open/closed/all), and labels (array of strings) properties.
    export const listIssuesSchema = {
      type: 'object',
      properties: {
        path: {
          type: 'string',
          description: 'Gitリポジトリの絶対パス',
        },
        state: {
          type: 'string',
          enum: ['open', 'closed', 'all'],
          description: 'issueの状態',
        },
        labels: {
          type: 'array',
          items: {
            type: 'string',
          },
          description: 'フィルタリングするラベル',
        },
      },
      required: [],
    };
  • src/server.ts:41-45 (registration)
    Registration of the 'list_issues' tool with the MCP server, including its description and inputSchema reference via ListToolsRequestSchema.
    {
      name: 'list_issues',
      description: 'カンバンボードのissue一覧を取得します',
      inputSchema: listIssuesSchema,
    },
  • The tool dispatch case in handleToolRequest that routes 'list_issues' requests to handleListIssues, extracting path, state, and labels from arguments.
    case 'list_issues':
      return await handleListIssues({
        path: args.path as string,
        state: args?.state as 'open' | 'closed' | 'all',
        labels: args?.labels as string[],
      });
  • IssueArgs interface defining the TypeScript types used by the list_issues handler (path, state, labels).
    export interface IssueArgs {
      path: string;  // Gitリポジトリの絶対パス
      state?: 'open' | 'closed' | 'all';
      labels?: string[];
    }
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 only states it retrieves a list, but does not disclose behavioral traits such as whether it is read-only (implied but not explicit), pagination, ordering, or any side effects. The description is insufficient for an agent to understand side effects or constraints.

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 a single sentence that is to the point and front-loaded with the action. It is concise and contains no filler. However, it could benefit from additional context while remaining efficient.

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 tool has 3 parameters, no output schema, and no annotations, the description is too minimal. It does not explain the output format or behavior (e.g., whether it returns all issues or paginated). The mention of Kanban board adds some context, but overall it lacks completeness for effective use.

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 the schema already documents the three parameters clearly. The tool description adds no additional meaning beyond the schema, meeting the baseline. It does not compensate for any gaps, but none exist.

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 '取得する' (get) and resource 'issue一覧' (list of issues) in the context of 'カンバンボード' (Kanban board). It distinguishes from sibling tools (add_comment, create_issue, update_issue) which are mutating. However, it does not explicitly state that it is read-only or mention filtering capabilities beyond the schema.

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. It does not specify prerequisites, scenarios, or explicitly exclude other tools. Siblings are mentioned in context signals but not referenced in the description.

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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