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etheaven
by etheaven

batch-codex

Execute multiple code tasks sequentially through Codex for mass refactoring, bulk changes, or automated transformations.

Instructions

Run multiple tasks through OpenAI Codex in batch. Use when the user wants Codex to handle several tasks sequentially — mass refactoring, bulk code changes, or automated transformations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tasksYesArray of atomic tasks to delegate to Codex
modelNoModel ID. Recommended order: gpt-5.4 (default), gpt-5.3-codex (coding), gpt-5.2-codex, gpt-5.2, gpt-5.1, gpt-5, gpt-5-mini.
reasoningEffortNoReasoning effort: none, minimal, low, medium, high, xhigh.
sandboxNoSandbox mode: read-only, workspace-write, danger-full-accessworkspace-write
parallelNoExecute tasks in parallel (experimental)
stopOnErrorNoStop execution if any task fails
timeoutNoMaximum execution time per task in milliseconds
workingDirNoWorking directory for execution
searchNoEnable web search for all tasks (activates web_search_request feature)
ossNoUse local Ollama server
enableFeaturesNoEnable feature flags
disableFeaturesNoDisable feature flags
Behavior3/5

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

With no annotations provided, the description must cover behavioral traits. It mentions 'batch' and 'sequential' execution, implying multiple tasks. However, it does not disclose potential side effects, authentication needs, rate limits, or what happens on failure. The 'automated transformations' hint at code changes, but this is 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 concise: two sentences front-load the purpose and usage, with no wasted words. Every sentence adds value.

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?

Despite high schema coverage, the tool has 12 parameters and no output schema. The description does not explain return behavior, error handling, or how parallel/stopOnError work. This leaves gaps for an agent selecting the tool.

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 description coverage is 100%, so the description does not need to detail each parameter. The description mentions 'several tasks' and 'mass refactoring,' which aligns with the 'tasks' parameter but adds little beyond the schema. Baseline of 3 is appropriate.

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's purpose: 'Run multiple tasks through OpenAI Codex in batch.' It specifies the verb ('run'), the resource ('OpenAI Codex'), and the batch nature, distinguishing it from single-task siblings like 'ask-codex'.

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 usage context: 'Use when the user wants Codex to handle several tasks sequentially.' It gives examples like mass refactoring and bulk code changes. However, it does not explicitly mention when not to use this tool or name alternative tools for single tasks.

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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