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bbernstein

LacyLights MCP Server

by bbernstein

create_project

Initiate a new lighting project by specifying a name and description to organize and manage theatrical lighting design workflows on the LacyLights MCP Server.

Instructions

Create a new lighting project

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
descriptionNoProject description
nameYesProject name

Implementation Reference

  • The core handler function for the 'create_project' tool. Parses input using Zod schema, calls GraphQL client to create project, returns formatted response with project details and success message, handles errors.
    async createProject(args: z.infer<typeof CreateProjectSchema>) {
      const { name, description} = CreateProjectSchema.parse(args);
    
      try {
        const project = await this.graphqlClient.createProject({
          name,
          description
        });
    
        return {
          project: {
            id: project.id,
            name: project.name,
            description: project.description,
            createdAt: project.createdAt
          },
          message: `Successfully created project "${name}"`
        };
      } catch (error) {
        throw new Error(`Failed to create project: ${error}`);
      }
    }
  • Zod input schema used for validating arguments in the createProject handler.
    const CreateProjectSchema = z.object({
      name: z.string().describe('Project name'),
      description: z.string().optional().describe('Project description')
    });
  • src/index.ts:97-113 (registration)
    Tool metadata registration (name, description, inputSchema) returned by ListToolsRequestHandler.
      name: "create_project",
      description: "Create a new lighting project",
      inputSchema: {
        type: "object",
        properties: {
          name: {
            type: "string",
            description: "Project name",
          },
          description: {
            type: "string",
            description: "Project description",
          },
        },
        required: ["name"],
      },
    },
  • src/index.ts:1804-1816 (registration)
    Dispatch handler in CallToolRequestSchema switch statement that invokes the createProject method.
    case "create_project":
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(
              await this.projectTools.createProject(args as any),
              null,
              2,
            ),
          },
        ],
      };
  • GraphQL client helper method that executes the createProject mutation and returns the new project data.
    async createProject(input: {
      name: string;
      description?: string;
    }): Promise<Project> {
      const mutation = `
        mutation CreateProject($input: CreateProjectInput!) {
          createProject(input: $input) {
            id
            name
            description
            createdAt
            updatedAt
          }
        }
      `;
    
      const data = await this.query(mutation, { input });
      return data.createProject;
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. 'Create a new lighting project' implies a write operation, but it doesn't disclose permissions needed, side effects, error conditions, or what happens on success (e.g., returns a project ID). This is a significant gap for a mutation tool with zero annotation coverage.

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 with zero waste. It's front-loaded with the core action and resource, making it easy to scan and understand quickly without unnecessary elaboration.

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 of a creation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, how to handle errors, or any behavioral nuances, leaving the agent with insufficient information to use it effectively beyond the basic schema.

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 both parameters ('name' and 'description') with their types and requirements. The description adds no parameter-specific information beyond what the schema provides, such as constraints or examples, so it meets the baseline for high schema coverage.

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 lighting project'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'create_cue_sequence' or 'create_fixture_instance' that also create resources, so it lacks sibling distinction.

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, context, or exclusions, such as when to use 'create_project' versus 'update_project' (if it existed) or how it relates to sibling tools like 'list_projects' or 'delete_project'.

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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