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get_stack_overview

Retrieve structured JSON data showing all tasks and their relationships in your hierarchical task management system to maintain context and organization.

Instructions

Get structured data of your entire task stack (JSON format with all task details and relationships)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The MCP tool handler function that executes the get_stack_overview tool by delegating to TaskManager.get_stack_overview()
    async def handle_get_stack_overview(self) -> Dict[str, Any]:
        return self.task_manager.get_stack_overview()
  • The input/output schema definition for the get_stack_overview tool, defined in AidderallHandlers.get_tool_definitions(), with no required input parameters.
    Tool(
        name="get_stack_overview",
        description="Get structured data of your entire task stack (JSON format with all task details and relationships)",
        inputSchema={"type": "object", "properties": {}},
    ),
  • src/server.py:66-66 (registration)
    Registration of the get_stack_overview tool handler in the server's call_tool dispatcher map.
    "get_stack_overview": handlers.handle_get_stack_overview,
  • Supporting method in TaskManager that generates the detailed JSON overview of the entire task stack, including zen state, depth, current task ID, all global tasks with subtasks, and completed count.
    def get_stack_overview(self) -> Dict[str, Any]:
        return {
            "zen_state": self.is_zen_state,
            "stack_depth": self.get_stack_depth(),
            "current_task_id": self.current_task.id if self.current_task else None,
            "global_tasks": [
                {
                    "id": task.id,
                    "title": task.title,
                    "status": task.status.value,
                    "created_at": task.created_at.isoformat(),
                    "completed_at": (
                        task.completed_at.isoformat() if task.completed_at else None
                    ),
                    "sub_tasks": [
                        {
                            "id": sub.id,
                            "title": sub.title,
                            "status": sub.status.value,
                            "created_at": sub.created_at.isoformat(),
                            "completed_at": (
                                sub.completed_at.isoformat()
                                if sub.completed_at
                                else None
                            ),
                        }
                        for sub in task.sub_tasks
                    ],
                }
                for task in self.global_tasks
            ],
            "completed_count": len(self.completed_tasks),
        }
Behavior2/5

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

With no annotations, the description carries full burden. It states the output format (JSON) and scope (all task details and relationships), but lacks behavioral details such as performance characteristics, rate limits, authentication needs, or whether it's read-only (implied by 'Get' but not explicit).

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 ('Get structured data of your entire task stack') and adds essential format details. Every word earns its place with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (read-only overview with no parameters) and lack of annotations/output schema, the description is minimally adequate. It covers the purpose and output format but misses behavioral context and usage guidelines, leaving gaps for an agent to infer.

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 no parameter documentation is needed. The description doesn't add param info, but this is appropriate given the empty schema, meeting the baseline for zero parameters.

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 ('Get') and resource ('structured data of your entire task stack'), specifying the format ('JSON format with all task details and relationships'). It distinguishes from siblings like 'get_current_task' or 'get_completed_tasks' by emphasizing 'entire' scope, but doesn't explicitly contrast them.

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 like 'get_big_picture' or 'get_current_task'. The description implies a comprehensive overview, but doesn't specify use cases, prerequisites, 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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