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Glama

debate_task

Delegate a task to multiple assistants to generate competing analyses, then compare their responses for better decisions.

Instructions

Delegate a task to multiple assistants for competing analyses.

Args: assistant_ids: JSON list of assistant ids. task: The task/instruction. context: JSON object of additional context. timeout: Per-task timeout in seconds. depth: Current delegation depth.

Returns: JSON: {"ok": true, "tasks": [...]}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYes
depthNo
contextNo{}
timeoutNo
assistant_idsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

C2.9/5.0
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. It doesn't disclose whether the call blocks, whether it spawns retrievable child tasks (list_tasks/get_task), auth requirements, rate limits, or what 'depth' recursion implies. The Args list is largely a restatement of parameter names with thin behavioral context.

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?

Front-loaded purpose followed by compact Args and Returns blocks. Reasonably sized with little padding, though the Args lines are terse to the point of adding minimal information.

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?

This is a multi-param task-orchestration tool with no annotations and numerous closely related siblings, so the description should do more. It omits alternative-tool routing, recursion/depth behavior, and blocking/async semantics, leaving significant gaps despite an output schema covering return values.

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 coverage is 0%, so the description must compensate. It partially does: it clarifies that assistant_ids is a JSON list and context is a JSON object even though the schema types them as plain strings, and it explains timeout as per-task and depth as delegation depth. However, formats, defaults, and the recursion/depth semantics remain underspecified for a 5-param tool.

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?

States a specific verb (delegate) and resource (task) with a differentiating scope: 'multiple assistants for competing analyses.' An agent can infer this differs from single-delegation or parallel execution siblings, but the description never names delegate_task or parallel_task to make the contrast explicit.

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 when-to-use guidance is given. It does not say when to prefer this over delegate_task, parallel_task, pipeline_task, or review_task, nor does it state prerequisites or expected call context. The 'competing analyses' phrase implies intent but stops short of routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.