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list_forms

Retrieve all forms from your Tally workspace to view and manage your form collection directly through AI conversation.

Instructions

List all forms in the workspace

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The core handler function for the 'list_forms' tool. It logs the input arguments and delegates to TallyApiService.getForms() to retrieve the list of forms.
    public async execute(args: FormRetrievalArgs): Promise<TallyFormsResponse> {
      console.log(`Executing form retrieval tool with args: ${JSON.stringify(args)}`);
      return this.tallyApiService.getForms(args);
    }
  • TypeScript interface defining the input parameters for the list_forms tool handler (page, limit, workspaceId).
    export interface FormRetrievalArgs {
      page?: number;
      limit?: number;
      workspaceId?: string;
    }
  • Instantiates the FormRetrievalTool class (as 'form_retrieval') along with other tools, using TallyApiClientConfig.
      workspaceManagement: new WorkspaceManagementTool(apiClientConfig),
      template: new TemplateTool(),
      form_creation: new FormCreationTool(apiClientConfig),
      form_modification: new FormModificationTool(apiClientConfig),
      form_retrieval: new FormRetrievalTool(apiClientConfig),
      form_sharing: new FormSharingTool(tallyApiClient),
      form_permissions: new FormPermissionManager(apiClientConfig),
      submission_analysis: new SubmissionAnalysisTool(apiClientConfig),
      diagnostic: new DiagnosticTool(),
    };
  • Registers/dispatches the 'list_forms' tool call by invoking this.tools.form_retrieval.execute() and formatting the response as MCP content.
    case 'list_forms':
      if (this.tools?.form_retrieval) {
        const forms = await this.tools.form_retrieval.execute(args || {});
        return {
          content: [
            {
              type: 'text',
              text: JSON.stringify(forms, null, 2)
            }
          ]
        };
      }
      return {
        content: [
          {
            type: 'text',
            text: 'Form retrieval functionality is not implemented'
          }
        ]
      };
  • JSON Schema definition for the 'list_forms' tool exposed via MCP tools/list endpoint (uses limit/offset pagination).
      name: 'list_forms',
      description: 'List all forms in the authenticated user\'s Tally account',
      inputSchema: {
        type: 'object',
        properties: {
          limit: { type: 'number', description: 'Maximum number of forms to return', minimum: 1, maximum: 100 },
          offset: { type: 'number', description: 'Number of forms to skip for pagination', minimum: 0 }
        }
      }
    },
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 it 'lists all forms' but doesn't describe return format, pagination behavior, permission requirements, or rate limits. For a list operation with zero annotation coverage, this leaves significant behavioral gaps.

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 for a simple list operation and front-loads the essential information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter list tool without annotations or output schema, the description is minimally adequate but lacks important context. It doesn't explain what information is returned about each form, whether results are paginated, or how this differs from sibling tools, leaving the agent with incomplete understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, maintaining focus on the tool's purpose. A baseline of 4 is appropriate for zero-parameter tools.

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 ('List') and resource ('forms in the workspace'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_form' or 'analyze_submissions', which would require specifying this lists ALL forms without filtering options.

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_form' (for single form details) or 'analyze_submissions' (for form data analysis). It lacks any context about prerequisites, filtering limitations, or appropriate use cases.

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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