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ask_chatgpt

Send a self-contained instruction to have ChatGPT analyze repository files and return cited paths. Conversation history is managed automatically; no need to paste context.

Instructions

Interpella un agente ChatGPT su questo repository e restituisce la sua risposta. Non può modificare file. Adatto a revisioni, secondi pareri, analisi. 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

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries the full behavioral burden and does it well: it states the tool cannot modify files, that ChatGPT sees the repository on disk, that file paths should be cited, and that conversation context is rebuilt by the bridge. This goes beyond a generic 'ask' tool and sets correct expectations.

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?

Every sentence earns its place: the operation, the key limitation, suitable use cases, file-path guidance, and context behavior are all covered in four concise sentences. The most important information is front-loaded.

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?

For a two-parameter tool with no output schema, the description is complete: it explains what to do, when to use it, what it cannot do, how to phrase instructions, and how conversation state works. Nothing needed to invoke it correctly is missing.

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 value by telling users to cite files by path when writing instructions, and by explaining that conversation context is reconstructed automatically, which directly informs how to use thread_id. This extra guidance justifies a 4.

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 action: interrogate a ChatGPT agent on the repository and return its response. It also differentiates from the sibling ask_chatgpt_write by explicitly noting that it cannot modify files. The scope and resource are both specific and unambiguous.

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 names suitable use cases (reviews, second opinions, analysis) and explicitly excludes file modification, which implies the write sibling is for modification tasks. It does not explicitly name ask_chatgpt_write as the alternative, so it falls just short of a 5.

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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