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spix_playbook_language_list

Retrieve available languages for phone and voice operations to configure communication settings in the Spix environment.

Instructions

List supported languages

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The `create_tool_handler` function is the universal handler that executes all MCP tools, including 'spix_playbook_language_list', by dynamically resolving the tool name to a `CommandSchema` and dispatching the request to the backend API.
    async def create_tool_handler(
        session: McpSessionContext,
        tool_name: str,
        arguments: dict,
    ) -> list:
        """Execute an MCP tool call by dispatching to the backend API.
    
        This function:
        1. Resolves the tool name to a command schema
        2. Validates session scope (playbook access, channel access)
        3. Builds the API request
        4. Dispatches to the backend
        5. Returns the response as MCP TextContent
    
        Args:
            session: The MCP session context for scope validation.
            tool_name: The MCP tool name (e.g., "spix_playbook_create").
            arguments: The tool arguments from the MCP client.
    
        Returns:
            List containing a single TextContent with the JSON response.
        """
        # Import here to avoid circular imports and handle missing mcp package
        try:
            from mcp.types import TextContent
        except ImportError:
            # Fallback for when mcp is not installed
            class TextContent:  # type: ignore[no-redef]
                def __init__(self, type: str, text: str) -> None:
                    self.type = type
                    self.text = text
    
        # Resolve tool name to schema
        schema = get_schema_by_tool_name(tool_name)
        if not schema:
            return [
                TextContent(
                    type="text",
                    text=orjson.dumps(
                        {"ok": False, "error": {"code": "unknown_tool", "message": f"Unknown tool: {tool_name}"}}
                    ).decode(),
                )
            ]
    
        # Validate tool access (not disabled)
        try:
            session.validate_tool_access(schema.path)
        except Exception as e:
            from spix_mcp.session import McpScopeError
    
            if isinstance(e, McpScopeError):
                return [TextContent(type="text", text=orjson.dumps({"ok": False, "error": e.to_dict()}).decode())]
            raise
    
        # Validate channel access if applicable
        channel = infer_channel_from_tool(schema.path)
        if channel:
            try:
                session.validate_channel_access(channel)
            except Exception as e:
                from spix_mcp.session import McpScopeError
    
                if isinstance(e, McpScopeError):
                    return [TextContent(type="text", text=orjson.dumps({"ok": False, "error": e.to_dict()}).decode())]
                raise
    
        # Handle playbook_id: validate and apply default
        playbook_id = arguments.get("playbook_id")
        try:
            effective_playbook = session.validate_playbook_access(playbook_id)
            if effective_playbook and not playbook_id:
                # Apply default playbook
                arguments["playbook_id"] = effective_playbook
        except Exception as e:
            from spix_mcp.session import McpScopeError
    
            if isinstance(e, McpScopeError):
                return [TextContent(type="text", text=orjson.dumps({"ok": False, "error": e.to_dict()}).decode())]
            raise
    
        # Build endpoint URL with path parameters
        endpoint, remaining_args = build_endpoint_url(schema, arguments)
    
        # Dispatch to backend API
        client = session.client
        method = schema.http_method.lower()
    
        if method == "get":
            response = await asyncio.to_thread(client.get, endpoint, params=remaining_args if remaining_args else None)
        elif method == "post":
            response = await asyncio.to_thread(client.post, endpoint, json=remaining_args if remaining_args else None)
        elif method == "patch":
            response = await asyncio.to_thread(client.patch, endpoint, json=remaining_args if remaining_args else None)
        elif method == "delete":
            response = await asyncio.to_thread(client.delete, endpoint, params=remaining_args if remaining_args else None)
        else:
            response = await asyncio.to_thread(client.get, endpoint)
    
        # Build response envelope
        envelope: dict = {"ok": response.ok, "meta": response.meta}
        if response.ok:
            envelope["data"] = response.data
            if response.pagination:
                envelope["pagination"] = response.pagination
            if response.warnings:
                envelope["warnings"] = response.warnings
        else:
            envelope["error"] = response.error
    
        return [TextContent(type="text", text=orjson.dumps(envelope).decode())]
  • The 'spix_playbook_language_list' tool is defined here as a `CommandSchema` within the `COMMAND_REGISTRY`, specifying its API endpoint (`/playbooks/languages`) and HTTP method (`GET`).
        path="playbook.language.list",
        cli_usage="spix playbook language list",
        http_method="GET",
        api_endpoint="/playbooks/languages",
        mcp_expose="tool",
        mcp_profile="safe",
        description="List supported languages",
    ),
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It states the action ('List') but doesn't describe what the output looks like (e.g., format, structure), whether it's paginated, or any error conditions. This is inadequate for a 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 with zero wasted words. It's front-loaded with the core action and resource, making it easy to parse and understand immediately.

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 no annotations and no output schema, the description is incomplete. It doesn't explain what 'supported languages' means in this context (e.g., for playbooks, calls, or other features), the return format, or any behavioral aspects. For a tool with no structured output documentation, this leaves significant gaps.

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 semantics, and it correctly implies no inputs are required, earning a baseline score of 4 for this context.

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 'List supported languages' clearly states the verb ('List') and resource ('supported languages'), making the purpose immediately understandable. However, it doesn't distinguish this from sibling tools like 'spix_playbook_emotion_list' or 'spix_playbook_voice_list' which also list playbook-related items, so it lacks 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 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. There's no mention of prerequisites, context (e.g., for configuring playbooks), or exclusions, leaving the agent to infer usage from the tool name alone.

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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