Skip to main content
Glama

create_project_column

Add a new column to a GitHub project by specifying the repository owner, repository name, project number, and column name for organized task management.

Instructions

Create a new column in a project

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesName of the column
ownerYesRepository owner (username or organization)
project_numberYesThe project number
repoYesRepository name

Implementation Reference

  • The async function that implements the core logic of the 'create_project_column' tool. It retrieves the project ID using getProject and then sends a POST request to the GitHub API to create a new project column.
    export async function createProjectColumn(owner: string, repo: string, projectNumber: number, name: string) {
        try {
            // Trước tiên cần lấy project_id từ project_number
            const project = await getProject(owner, repo, projectNumber);
    
            // Tạo cột với project_id
            const url = `https://api.github.com/projects/${project.id}/columns`;
    
            const response = await githubRequest(url, {
                method: 'POST',
                body: {
                    name: name,
                },
                headers: {
                    'Accept': 'application/vnd.github.inertia-preview+json'
                }
            });
    
            return response;
        } catch (error) {
            if (error instanceof GitHubError) {
                throw error;
            }
    
            throw new GitHubError(`Failed to create project column: ${(error as Error).message}`, 500, { error: (error as Error).message });
        }
    }
  • Zod schema defining the input parameters and validation for the create_project_column tool.
    export const CreateProjectColumnSchema = z.object({
        owner: z.string().describe("Repository owner (username or organization)"),
        repo: z.string().describe("Repository name"),
        project_number: z.number().describe("The project number"),
        name: z.string().describe("Name of the column"),
    });
  • index.ts:226-228 (registration)
    Registration of the tool in the ListTools response, including name, description, and input schema reference.
    name: "create_project_column",
    description: "Create a new column in a project",
    inputSchema: zodToJsonSchema(projects.CreateProjectColumnSchema),
  • Handler dispatch in the main CallToolRequest switch statement that validates input and invokes the projects.createProjectColumn function.
    case "create_project_column": {
      const args = projects.CreateProjectColumnSchema.parse(request.params.arguments);
      const result = await projects.createProjectColumn(
        args.owner,
        args.repo,
        args.project_number,
        args.name
      );
      return {
        content: [{ type: "text", text: JSON.stringify(result, null, 2) }],
      };
    }
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a creation operation, implying it's a write/mutation tool, but doesn't mention permission requirements, rate limits, whether it's idempotent, or what happens on success/failure. This leaves significant behavioral gaps for an agent.

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 communicates the core purpose without any wasted words. It's appropriately sized and front-loaded with the essential information.

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?

For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after creation (e.g., returns column ID, error conditions), permission requirements, or how it differs from similar tools. The 100% schema coverage helps but doesn't compensate for the missing behavioral context.

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 all 4 parameters thoroughly. The description adds no additional parameter context beyond what's in the schema, meeting the baseline expectation but not providing extra value.

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 action ('Create') and resource ('new column in a project'), making the purpose immediately understandable. However, it doesn't distinguish this tool from similar siblings like 'create_project' or 'update_project_column', which would require explicit differentiation for a perfect score.

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 'update_project_column' or 'list_project_columns', nor does it mention prerequisites or contextual constraints. It simply states what the tool does without usage instructions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Related Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/tuanle96/mcp-github'

If you have feedback or need assistance with the MCP directory API, please join our Discord server