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ask_chatgpt_write

Ask ChatGPT to modify files in this repository. Provide an instruction to fix code, refactor, or create new files; ChatGPT writes changes directly to disk using the maintained conversation context.

Instructions

Chiede a ChatGPT di modificare file in questo repository (fix, refactor, nuovo codice). PUÒ scrivere su disco. ChatGPT vede questo repository su disco, quindi cita i file per percorso. Il contesto della conversazione viene ricostruito dal bridge: non serve incollarlo.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
thread_idNoIdentificatore della conversazione. Omettilo per iniziare un thread nuovo; riusa quello restituito dalla chiamata precedente per continuare lo stesso discorso mantenendo il contesto.
instructionYesIstruzione completa e autosufficiente.
Install Server

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it does this well by explicitly warning 'PUÒ scrivere su disco' and noting that ChatGPT sees the repository on disk. It does not cover permissions, reversibility, or return behavior, but the critical write-side-effect is clearly disclosed.

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 and well-structured: purpose first, then the critical write warning, then file-path guidance, then context-handling guidance. Every sentence adds a distinct, necessary fact and there is no filler.

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?

For a simple two-parameter tool with full schema coverage, the description covers purpose, side effects, and invocation guidance. The main gap is that it does not explicitly describe the return value, though the schema's thread_id hint implies a returned thread identifier. Overall it is complete enough for an agent to call it correctly.

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 100%, so the baseline is 3. The description adds genuine value for the 'instruction' parameter by specifying that file paths should be cited and that conversation context should not be pasted. No extra thread_id semantics are needed because the schema already describes that parameter fully.

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 states a specific action ('Chiede a ChatGPT di modificare file in questo repository') and a clear resource (files in this repository), with examples (fix, refactor, new code). The explicit warning that it CAN write to disk and the '_write' suffix distinguish it from the sibling 'ask_chatgpt'.

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 gives clear context for when to use the tool: when ChatGPT should modify files in the repo. It also provides practical invocation guidance—cite files by path, and do not paste conversation context because the bridge reconstructs it. It does not explicitly name 'ask_chatgpt' as the alternative, so exclusion guidance is absent.

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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