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jhliberty

Basecamp MCP Server

by jhliberty

update_column

Modify the title of a specific column within a Basecamp project by specifying the project ID, column ID, and the new title to ensure accurate project organization.

Instructions

Update a column title

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
column_idYesThe column ID
project_idYesThe project ID
titleYesThe new column title

Implementation Reference

  • src/index.ts:243-255 (registration)
    Registration of the 'update_column' tool in the MCP server, defining its name, description, and input schema.
    {
      name: 'update_column',
      description: 'Update a column title',
      inputSchema: {
        type: 'object',
        properties: {
          project_id: { type: 'string', description: 'The project ID' },
          column_id: { type: 'string', description: 'The column ID' },
          title: { type: 'string', description: 'The new column title' },
        },
        required: ['project_id', 'column_id', 'title'],
      },
    },
  • The handler function in BasecampClient that executes the column update by making a PUT request to the Basecamp API.
    async updateColumn(projectId: string, columnId: string, title: string): Promise<Column> {
      const response = await this.client.put(`/buckets/${projectId}/card_tables/columns/${columnId}.json`, {
        title,
      });
      return response.data;
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Update' implies a mutation, but the description doesn't state whether this requires specific permissions, what happens on success/failure, or if changes are reversible. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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 extremely concise at just three words, with zero wasted language. It's front-loaded with the core action and resource, making it easy to parse quickly. This is an example of efficient communication.

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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, error conditions, or behavioral aspects like side effects. For a tool that modifies data, more context is needed to use it 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%, with all three parameters (column_id, project_id, title) documented in the schema. The description adds no additional parameter semantics beyond implying that 'title' is the attribute being updated. This meets the baseline of 3 when the schema does the heavy lifting.

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 ('Update') and resource ('a column title'), making the tool's purpose understandable. It distinguishes from sibling tools like 'update_column_color' by focusing on title changes rather than color. However, it doesn't specify the scope (e.g., within a project) which could make it slightly less specific than a perfect 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. It doesn't mention prerequisites, when not to use it, or differentiate from similar tools like 'update_column_color' or 'move_column'. This lack of context leaves the agent to infer usage based on the name alone.

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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