The Clarification Request Tool
When a request is ambiguous, have the agent ask a focused clarifying question rather than assume — turning a likely wrong answer into the right one with a single well-placed prompt.
Autonomous agents fail quietly
An agent that can act is only useful if it remembers, plans, and checks its own work. Without a cognitive core, agents forget context, skip steps, and state wrong answers with full confidence — and you find out too late.
No memory across runs
Agents start from zero every session, re-asking what they were already told.
Acting before thinking
Without an explicit plan, agents take the first path, not the right one.
Confident wrong answers
Nothing checks the output, so mistakes ship as if they were facts.
No accountability
When it goes wrong, there is no trace of why the agent did what it did.
Clarification Request, without the risk
Capability
What it does
Let agents ask instead of guessing.
it pauses to ask the user a focused clarifying question when the request is ambiguous.
- Detects ambiguity
- Asks one focused question
- Offers interpretations
- Acts on the answer
Assignable to any agent
How it works
Predictable, inspectable behavior
Designed to be reliable.
the agent surfaces the specific ambiguity and candidate interpretations and waits for an answer, so it acts on intent instead of a guess.
Every call logged
Governance
Private, governed, on-premise
Runs inside your perimeter.
This tool runs inside your perimeter, scoped per user with full audit logging, so the agent’s reasoning, memory, and decisions stay private and accountable — never sent to a third-party service.
Per-tenant, logged
Parameters
The clarification_request tool accepts these inputs when an agent calls it. Required inputs are flagged.
Where Clarification Request pays back
Ambiguous asks
Confirm which "report" or "account" the user means before acting.
Missing inputs
Ask for a date range or scope the task actually needs.
High stakes
Double-check intent before an expensive or irreversible step.
Fewer redos
Get it right the first time instead of guessing and redoing.
Assigned to agents, orchestrated as networks
On VDF AI, an industry’s use cases map to agents, and you assign tools like this one to those agents. Compose multiple agents into a governed, on-premise network.
What changes after you assign it
Questions about the Clarification Request tool
What is the Clarification Request tool?
It pauses to ask the user a focused clarifying question when the request is ambiguous. Assigned to a VDF AI agent, it runs under role-based policy with full audit logging so the capability is safe to use in production.
How is this different from human approval?
Clarification gathers missing intent; human approval authorizes a specific proposed action. Agents often use both.
Does it reduce hallucination?
Yes — asking instead of assuming is one of the most effective ways to prevent confidently wrong answers on ambiguous requests.
Does it run on-premise?
Yes. Like every VDF AI tool, it can run on-premise or in your sovereign cloud, scoped per user and audit-logged, so your data never leaves your perimeter.
How do agents use it?
You assign the tool to an agent under a role-based policy; the agent calls it as one step in a task, and several agents and tools can be orchestrated together as a governed VDF AI Network.
Tools that work well alongside this one
Where this tool delivers value
Put Clarification Request to work
See the Clarification Request tool assigned to an agent and orchestrated in a governed, on-premise network.