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send_reply

Send visible replies or internal admin notes to conversations in the Cuti-E platform to manage user feedback and communication.

Instructions

Send a reply message in a conversation. Can be a visible reply or an internal note.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
conversation_idYesThe conversation ID to reply to
messageYesThe message text
is_internal_noteNoIf true, message is only visible to admins (default: false)

Implementation Reference

  • The handler logic for 'send_reply', which sends a POST request to the API to create a message in a conversation.
    case "send_reply": {
      const body = { message: args.message };
      if (args.is_internal_note) body.is_internal_note = true;
      result = await apiRequest("POST", `/v1/conversations/${args.conversation_id}/messages`, { body });
      break;
    }
  • The tool definition and input schema for 'send_reply'.
    {
      name: "send_reply",
      description:
        "Send a reply message in a conversation. Can be a visible reply or an internal note.",
      inputSchema: {
        type: "object",
        properties: {
          conversation_id: {
            type: "string",
            description: "The conversation ID to reply to",
          },
          message: {
            type: "string",
            description: "The message text",
          },
          is_internal_note: {
            type: "boolean",
            description: "If true, message is only visible to admins (default: false)",
          },
        },
        required: ["conversation_id", "message"],
      },
    },
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the reply types but fails to cover critical aspects like required permissions, rate limits, whether the action is reversible, or what happens on success/failure. This is inadequate 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 that front-loads the core purpose and adds a useful detail about reply types. There is no wasted verbiage, making it appropriately sized and well-structured.

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 mutation tool with no annotations and no output schema, the description is incomplete. It lacks information on behavioral traits, error handling, and return values, which are essential for an agent to use this tool effectively in context.

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 input schema already documents all parameters thoroughly. The description adds no additional meaning beyond what the schema provides, such as explaining parameter interactions or constraints, meeting 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 verb ('Send') and resource ('a reply message in a conversation'), specifying it can be either visible or internal. However, it doesn't explicitly distinguish this from sibling tools like 'update_conversation', which might also involve sending messages, leaving some ambiguity.

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 such as 'update_conversation' or other messaging-related operations. It mentions the types of replies but offers no context on prerequisites, timing, or exclusions.

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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