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gemini_parallel

Execute multiple Gemini AI tasks concurrently within a shared workspace, with results saved to a designated file for efficient batch processing.

Instructions

Run multiple gemini tasks in parallel. All tasks share workspace/permission/save_file. Results are appended to save_file with XML wrappers (). Max 100 tasks. Model can be array: single element shared by all, or one per task.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceYesProject root directory. Boundary for 'workspace-write'. Use absolute paths or relative paths.
permissionNoSecurity level: 'read-only' (analyze files), 'workspace-write' (modify inside workspace), 'unlimited' (full system access). Default: 'read-only'.read-only
save_fileYesPREFERRED when agent needs to write files or produce lengthy output. Output is written directly to this path, avoiding context overflow. This write is permitted even in read-only mode (server-handled). Essential for: code generation, detailed reports, documentation.
report_modeNoGenerate a standalone, document-style report (no chat filler) suitable for sharing.
context_pathsNoList of relevant files/dirs to preload as context hints.
modelNoModel override(s). If single element, all tasks use that model. If multiple elements, must match parallel_prompts length - each task uses corresponding model. Empty array uses CLI default.
parallel_promptsYesComplete prompts for parallel execution. Each spawns an independent subprocess.
parallel_task_notesYesLabels for each task. Length MUST equal parallel_prompts.
parallel_max_concurrencyNoMax concurrent subprocesses.
parallel_fail_fastNoStop spawning new tasks when any fails (already running tasks continue).
debugNoEnable execution stats (tokens, duration) for this call.
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: results are appended to save_file with XML wrappers, tasks share workspace/permission/save_file, and model configuration options. However, it doesn't cover important aspects like error handling (beyond fail_fast), performance characteristics, or what happens when tasks exceed max concurrency.

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 appropriately sized with three sentences that each add value. It's front-loaded with the core purpose, followed by implementation details and configuration options. There's minimal waste, though the final sentence about model configuration could be slightly more concise.

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?

For a complex parallel execution tool with 11 parameters and no annotations or output schema, the description provides adequate but incomplete coverage. It explains the parallel nature and some behavioral aspects, but doesn't address error scenarios, output interpretation beyond XML wrappers, or how results from multiple tasks are organized in the save_file.

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?

With 100% schema description coverage, the schema already documents all 11 parameters thoroughly. The description adds minimal value beyond the schema - it mentions the model array behavior and max 100 tasks limit (which is also in the schema). The baseline of 3 is appropriate when the schema does the heavy lifting.

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 specific action ('Run multiple gemini tasks in parallel') and distinguishes it from its sibling 'gemini' by emphasizing parallel execution. It specifies the resource (gemini tasks) and scope (max 100 tasks, shared workspace/permission/save_file).

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 provides clear context for when to use this tool (parallel execution of multiple tasks) and implicitly distinguishes it from non-parallel alternatives like 'gemini'. However, it doesn't explicitly state when NOT to use it or name specific alternative tools for different scenarios.

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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