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qq418716640

BotBell MCP Server

botbell_get_replies

Fetch user replies from BotBell notifications to enable interactive AI conversations. Retrieve responses to your messages for processing follow-up actions.

Instructions

Check if the user has replied to your messages in the BotBell app. Messages are consumed on fetch (won't be returned again).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax number of replies to fetch (default 20, max 100)

Implementation Reference

  • Tool registration and handler implementation for 'botbell_get_replies' when bot_id is available.
    server.tool(
      "botbell_get_replies",
      "Check if the user has replied to messages in the BotBell app. " +
      (hasExtras
        ? "Use bot_id for your own bots or alias for external bots. "
        : "Use botbell_list_bots first to find the bot_id. ") +
      "Messages are consumed on fetch (won't be returned again).",
      repliesSchema,
      async (args) => {
        try {
          const { bot_id, alias, limit } = args as { bot_id?: string; alias?: string; limit: number };
    
          // Route via alias
          if (alias) {
            const btToken = resolveAlias(alias);
            if (!btToken) return errorResult(`Unknown alias "${alias}". Available: ${aliasNames.join(", ")}`);
            return await pollViaBotToken(btToken, apiBase, limit);
          }
    
          // Route via bot_id (PAT)
          if (!bot_id) return errorResult("Provide either bot_id or alias.");
          const result = await api("GET", `/bots/${bot_id}/replies?limit=${limit}`);
          if (!result.ok) return errorResult(`Failed to fetch replies: ${handleApiError(result)}`);
    
          const data = result.data.data as { messages: Array<Record<string, unknown>> };
          const messages = data.messages;
    
          if (!messages || messages.length === 0) {
            return textResult("No new replies.");
          }
    
          const text = messages.map(formatPollMessage).join("\n");
    
          return textResult(`${messages.length} new reply(s):\n\n${text}`);
        } catch (error) {
          return errorResult(`Error: ${error instanceof Error ? error.message : String(error)}`);
        }
      }
    );
  • Alternative tool registration and handler implementation for 'botbell_get_replies' for cases without bot_id.
    server.tool(
      "botbell_get_replies",
      "Check if the user has replied to your messages in the BotBell app. " +
      "Messages are consumed on fetch (won't be returned again).",
      repliesSchema,
      async (args) => {
        try {
          const { alias, limit } = args as { alias?: string; limit: number };
    
          if (alias) {
            const btToken = resolveAlias(alias);
            if (!btToken) return errorResult(`Unknown alias "${alias}". Available: ${aliasNames.join(", ")}`);
            return await pollViaBotToken(btToken, apiBase, limit);
          }
    
          return await pollViaBotToken(token, apiBase, limit);
        } catch (error) {
Behavior4/5

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

Since no annotations are provided, the description carries the full burden. It discloses a critical behavioral trait: 'Messages are consumed on fetch (won't be returned again)', which is essential for understanding the tool's side effects. However, it doesn't cover other potential behaviors like error conditions or authentication needs.

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 sentence states the purpose, and the second adds crucial behavioral context. It's appropriately sized and front-loaded with essential information.

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 no annotations and no output schema, the description does well by explaining the tool's purpose and a key behavioral trait. However, it lacks details on return values (e.g., format of replies) and doesn't cover all potential contexts like error handling, which could be important for a tool with side effects.

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?

The description doesn't mention the 'limit' parameter at all. However, the input schema has 100% description coverage, providing default, range, and meaning. With high schema coverage, the baseline score is 3, as the schema adequately documents the parameter without description assistance.

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 tool's purpose with a specific verb ('Check') and resource ('if the user has replied to your messages in the BotBell app'). It distinguishes from the sibling tool 'botbell_send' by focusing on fetching replies rather than sending messages.

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool ('Check if the user has replied to your messages'), but it doesn't explicitly mention when not to use it or name alternatives. The sibling tool 'botbell_send' is implied as complementary but not directly contrasted.

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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