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tsunamayo7

claude-code-codex-agents

by tsunamayo7

generate

Request code generation from Codex CLI (GPT-5.4) by providing a description, language, and optional working directory or output file.

Instructions

Codex CLI(GPT-5.4)にコード生成を依頼。

Args: description: 生成するコードの説明(日本語OK) language: プログラミング言語 cwd: 作業ディレクトリ output_file: 出力ファイルパス(空の場合はコードを返す)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cwdNo
languageNopython
descriptionYes
output_fileNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
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. It discloses a meaningful behavioral trait: if output_file is empty, the tool returns code; otherwise it likely writes to a file. However, it does not mention side effects, permissions, or safety implications beyond this, leaving some uncertainty about the tool's behavior.

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 short and efficient, starting with a one-line purpose statement followed by a clear parameter list. Every sentence serves a purpose with no extraneous information.

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

Completeness4/5

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

The description adequately covers the tool's purpose and all parameters, and it explains the behavior of the output_file parameter. Given that an output schema exists, the lack of explicit return value documentation is acceptable. However, it omits information about error handling, required environments, or typical use cases, which would make it more complete.

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

Parameters4/5

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

Schema coverage is 0%, but the description compensates by explaining each parameter: description (code spec, Japanese OK), language (programming language), cwd (working directory), and output_file (output path; empty returns code). This adds meaningful context beyond the schema's type and default fields, though it could be more detailed about allowed values or formats.

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 'Request code generation from Codex CLI (GPT-5.4)', which is a specific verb+resource combination. This distinguishes it from sibling tools like execute or review, as the focus is on generating code rather than running or explaining it.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The tool's purpose implies it should be used when code generation is needed, but there is no explicit guidance on when to use it versus alternatives like execute or discuss. The description does not mention exclusions or alternatives, so it relies on the verb and context for implied usage.

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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