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gotoHuman MCP

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list-forms

Retrieve all available review forms to integrate human approval steps into AI agents and automations. First, fetch form schemas using get-form-schema for field details.

Instructions

List all available review forms. NOTE: You need to fetch the schema for the form fields first using the get-form-schema tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Handler function for the 'list-forms' tool: creates a GotoHuman instance and fetches available review forms, returning them as JSON or error.
    async () => {
      try {
        const gotoHuman = new GotoHuman({origin: "mcp-server", originV: version});
        const forms = await gotoHuman.fetchReviewForms();
    
        return {
          content: [{
            type: "text",
            text: JSON.stringify({
              success: true,
              forms: forms
            })
          }]
        };
      } catch (error) {
        return {
          content: [{
            type: "text",
            text: JSON.stringify({
              success: false,
              error: error instanceof Error ? error.message : "Unknown error occurred"
            })
          }],
          isError: true
        };
      }
    }
  • src/index.ts:22-52 (registration)
    Registers the 'list-forms' tool using server.tool, with empty input schema and the handler function.
      "list-forms",
      "List all available review forms. NOTE: You need to fetch the schema for the form fields first using the get-form-schema tool.",
      {},
      async () => {
        try {
          const gotoHuman = new GotoHuman({origin: "mcp-server", originV: version});
          const forms = await gotoHuman.fetchReviewForms();
    
          return {
            content: [{
              type: "text",
              text: JSON.stringify({
                success: true,
                forms: forms
              })
            }]
          };
        } catch (error) {
          return {
            content: [{
              type: "text",
              text: JSON.stringify({
                success: false,
                error: error instanceof Error ? error.message : "Unknown error occurred"
              })
            }],
            isError: true
          };
        }
      }
    );
  • Empty input schema for the 'list-forms' tool (no parameters required).
    {},
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses a behavioral trait (the prerequisite to use 'get-form-schema' first), which adds useful context beyond basic functionality. However, it doesn't cover other aspects like rate limits, permissions, or return format, leaving some gaps in behavioral disclosure.

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 two sentences with zero waste: the first states the purpose, and the second provides critical usage guidance. It is front-loaded with the core function and efficiently adds necessary context, making it highly concise and well-structured.

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

Completeness4/5

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

Given the tool's simplicity (0 parameters, no annotations, no output schema), the description is complete enough for its purpose. It covers the main action and a key prerequisite, though it could be more comprehensive by mentioning what the output contains or any limitations. Without an output schema, some additional detail on return values might be helpful but isn't strictly required.

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 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description doesn't need to add parameter details, and it appropriately focuses on usage context. A baseline of 4 is applied for tools with no parameters, as the description compensates by providing relevant guidance.

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 ('List') and resource ('all available review forms'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'get-form-schema' beyond mentioning it as a prerequisite, so it doesn't reach the highest level of sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool by specifying a prerequisite: 'You need to fetch the schema for the form fields first using the get-form-schema tool.' This provides clear guidance on usage context and references an alternative tool, meeting the criteria for a top score.

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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