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spix_playbook_rule_list

Retrieve all rules associated with a specific playbook to manage automated workflows and actions within the Spix communication platform.

Instructions

List rules for a playbook

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
playbook_idYesPlaybook ID

Implementation Reference

  • The `create_tool_handler` function in `tools.py` handles the execution of all MCP tool calls by 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 `CommandSchema` definition for `playbook.rule.list` in `registry.py` defines the mapping from the MCP tool `spix_playbook_rule_list` to the backend API endpoint `/playbooks/{playbook_id}/rules`.
        path="playbook.rule.list",
        cli_usage="spix playbook rule list <playbook_id>",
        http_method="GET",
        api_endpoint="/playbooks/{playbook_id}/rules",
        mcp_expose="tool",
        mcp_profile="safe",
        description="List rules for a playbook",
        positional_args=[
            CommandParam("playbook_id", "string", required=True, description="Playbook ID"),
        ],
    ),
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'List rules for a playbook', which implies a read-only operation, but does not specify details like pagination, sorting, error handling, or authentication requirements. This leaves significant gaps in understanding how the tool behaves beyond its basic purpose.

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, direct sentence with no unnecessary words, making it highly concise and front-loaded. It efficiently communicates the core action without any fluff, earning a top score for brevity and clarity in structure.

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 lack of annotations and output schema, the description is incomplete for a tool that likely returns a list of rules. It does not explain what the output includes (e.g., rule details, formats) or any behavioral aspects like error cases. For a read operation with no structured support, more context is needed to be fully helpful.

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 input schema has 100% description coverage, with the 'playbook_id' parameter documented as 'Playbook ID'. The description does not add any additional meaning or context beyond what the schema provides, such as format examples or constraints. With high schema coverage, a baseline score of 3 is appropriate as the schema handles the parameter documentation adequately.

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 ('rules for a playbook'), making the purpose specific and understandable. However, it does not differentiate from sibling tools like 'spix_playbook_list' or 'spix_playbook_show', which might list playbooks themselves rather than their rules, leaving some ambiguity in sibling context.

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 whether it's for retrieving all rules or specific ones, or how it relates to other playbook-related tools like 'spix_playbook_rule_add'. There is no mention of prerequisites or exclusions, leaving usage unclear.

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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