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list_dashboards

List all dashboards in a base by providing the base app token.

Instructions

List all dashboards in a base

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
app_tokenYesBase app token

Implementation Reference

  • MCP tool handler for 'list_dashboards'. Calls client.listDashboards() and returns the results.
    case 'list_dashboards': {
      const dashboards = await client.listDashboards(args.app_token as string);
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify({
              success: true,
              count: dashboards.length,
              dashboards,
            }, null, 2),
          },
        ],
      };
    }
  • Tool schema definition for 'list_dashboards' in the MCP tools array. Defines input schema with required 'app_token' field.
    {
      name: 'list_dashboards',
      description: 'List all dashboards in a base',
      inputSchema: {
        type: 'object',
        properties: {
          app_token: {
            type: 'string',
            description: 'Base app token',
          },
        },
        required: ['app_token'],
      },
    },
  • The API client method that makes the actual HTTP GET request to the Lark bitable API to list dashboards.
    /**
     * List all dashboards in a base
     * @param appToken - Base app token
     */
    async listDashboards(appToken: string): Promise<any[]> {
      const response = await this.request<{ items: any[] }>({
        method: 'GET',
        url: `/bitable/v1/apps/${appToken}/dashboards`,
      });
      return response.data?.items || [];
    }
  • MCP server registration of tools via ListToolsRequestSchema handler. The tools array (including list_dashboards) is registered here.
    // Handle tool list requests
    server.setRequestHandler(ListToolsRequestSchema, async () => {
      return { tools };
    });
  • Alternative handler for 'list_dashboards' intent in the bot assistant. Uses listBlocks instead of listDashboards.
    private async handleListDashboards(
      intent: ParsedIntent,
      context: ConversationContext,
      chatId: string
    ): Promise<void> {
      const { appToken } = intent.entities;
    
      if (!appToken) {
        await this.sendMessage(chatId, '❓ I need an app token to list dashboards.');
        return;
      }
    
      try {
        const blocks = await this.dashboardClient.listBlocks(appToken);
    
        if (blocks.length === 0) {
          await this.sendMessage(chatId, '📋 No dashboards found in this base.');
          return;
        }
    
        const message = `📋 Found ${blocks.length} block(s):\n\n` +
          blocks.map((block: any, i: number) =>
            `${i + 1}. ${block.block_type || 'Unknown'} (ID: ${block.block_id})`
          ).join('\n');
    
        await this.sendMessage(chatId, message);
    
      } catch (error: any) {
        await this.sendMessage(chatId, `❌ Failed to list dashboards: ${error.message}`);
      }
    }
Behavior2/5

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

No annotations are present, and the description does not disclose any behavioral traits such as pagination, authentication requirements, performance characteristics, or whether it returns all dashboards or filtered results.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that efficiently conveys the tool's purpose without extraneous words. It is appropriately short for a simple list operation.

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 tool performs a list operation with no output schema, the description lacks details about return structure, pagination, error handling, or any other behavior needed for an agent 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 coverage is 100%, so the schema adequately describes the single parameter 'app_token'. The description adds no additional meaning beyond the schema, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'list' and the resource 'dashboards' with scope 'in a base', which is specific and distinguishes it from sibling tools like create_dashboard or delete_dashboard.

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?

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, limitations, or context for choosing between list_dashboards and other dashboard tools.

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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