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zen_parallel

Execute multiple command sequences concurrently, each sequence running serially in a separate tab, and collect results per sequence.

Instructions

Run command sequences in parallel — typically one sequence per tab.

Each inner list is a sequence that runs serially; all sequences run concurrently. Commands that target a specific tab (navigate, switchTab, or any tab-aware action) MUST include "tabId" inside the parallel batch to avoid race conditions over the active tab.

Returns a list of result lists, one per input sequence.

Args: sequences: List of command sequences. Each command is a dict with "action" and parameters — same shape as zen_batch commands. Example for driving two tabs at once: [ [{"action": "navigate", "url": "...", "tabId": 12}, {"action": "waitForElement", "selector": "h1", "tabId": 12}, {"action": "pageText", "tabId": 12}], [{"action": "navigate", "url": "...", "tabId": 13}, {"action": "waitForElement", "selector": "h1", "tabId": 13}, {"action": "pageText", "tabId": 13}] ]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sequencesYes
Behavior4/5

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

The description covers parallel execution, race condition warnings, and return format (list of result lists). With no annotations, it carries full burden. It lacks details on error handling or partial failure behavior, but the core behavioral traits are well communicated.

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?

Front-loaded with a concise summary, then a key warning, then return info, then parameter details. Every sentence adds value; no fluff. The example is well-placed. Structure is clean and efficient.

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 no output schema, the description adequately covers what the tool returns (list of result lists). It explains the complex input parameter in detail and provides a realistic use case. No critical gaps remain for the tool's intended use.

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%, but the description fully defines the 'sequences' parameter: it explains the structure (list of lists of command dicts), the command format (action + params, same as zen_batch), and provides a concrete example. This adds critical meaning beyond the minimal 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 the tool runs command sequences in parallel, one per tab, distinguishing it from serial batch execution. The verb 'run' and resource 'command sequences' are explicit, and the context of parallel vs serial is well-defined.

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 explicitly advises to include tabId in commands to avoid race conditions, which is critical guidance. It provides an example with tabId. However, it does not mention when not to use this tool or contrast with siblings like zen_batch or zen_workflow, missing a chance to clarify usage boundaries.

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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