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sipyourdrink-ltd

Bernstein - Multi-agent orchestration

bernstein_create_subtask

Create a subtask linked to a parent task by specifying goal, role, scope, priority, complexity, and time estimate. Automatically transitions parent to WAITING_FOR_SUBTASKS.

Instructions

Create a subtask linked to a parent task.

Agents call this to decompose their current work into subtasks during execution. The parent task is automatically transitioned to WAITING_FOR_SUBTASKS status.

Args: parent_task_id: ID of the parent task that this subtask belongs to. goal: Description of what the subtask should accomplish. role: Specialist role to assign (backend, frontend, qa, …). priority: 1=critical, 2=normal, 3=nice-to-have. scope: Task scope - small, medium, or large. complexity: Task complexity - low, medium, or high. estimated_minutes: Rough time estimate in minutes.

Returns: JSON with the created subtask ID, parent_task_id, title, and status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalYes
roleNoauto
scopeNomedium
priorityNo
complexityNomedium
parent_task_idYes
estimated_minutesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries full burden. It discloses the automatic status transition of the parent task to WAITING_FOR_SUBTASKS, a key behavioral trait beyond basic creation. This adds good transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a summary, usage context, parameter list, and return info. It is efficient, though the parameter list could be slightly more concise. No irrelevant sentences.

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

Completeness5/5

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

Given the tool's complexity (7 params, 2 required) and the presence of an output schema (context signal), the description covers all parameters, usage context, side effects, and return values. It is complete for an AI agent to correctly select and invoke the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate. It provides detailed explanations for all 7 parameters, including purpose, defaults, and types (e.g., priority ranges, role examples). This adds significant meaning beyond the schema.

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 'Create a subtask linked to a parent task' and explains its use for decomposing work. Among sibling tools, it is the only creation tool, making it easily distinguishable.

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 specifies when to call the tool ('decompose their current work into subtasks during execution') and notes the side effect on parent task status. However, it does not explicitly state when not to use it or mention alternatives among siblings.

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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