Agent Output Gate

A lightweight three-question filter that makes agents speak only when necessary, using human-like voice instead of status dumps.

What it is

Vox (@Voxyz_ai) proposed a simple output gate that agents apply before sending any message to users. The gate consists of three questions and a voice rule.

The three questions

1. Does the user need to know this, or is it an internal status update?
2. Would they miss something important if I stayed quiet?
3. Is saying it now helpful, or noise?

If all three answers are yes, the agent speaks in one sentence like a coworker. Otherwise, it stays silent.

Why it matters

Agent-heavy workflows produce overwhelming message volume. Users drown in status updates, progress reports, and internal deliberations that do not require human attention. An output gate reduces noise without reducing transparency, by forcing the agent to justify every message against user relevance.

Key points

• Human-like voice: When the gate passes, the agent uses a coworker-like tone rather than structured status dumps.
• One-sentence constraint: Forces concision. If the message cannot be compressed to one sentence, it may not be urgent enough to send.
• Silence as default: The gate inverts the default from "speak unless told not to" to "stay silent unless justified."
• Customizable to team culture: The voice examples can be adapted to match specific team communication styles.

Limitations

• Single-source pattern. Needs validation across different agent types and user preferences.
• May suppress useful context in debugging or learning scenarios where verbosity is desired.
• The "coworker voice" is vague and may not suit all domains (e.g., medical, legal, financial reporting).

Open questions

• How does the gate behave in high-stakes scenarios where missing information is costly?
• Can the three questions be reduced to a single relevance score, or does the sequential logic matter?
• Should the gate be a skill, a harness default, or a user-configurable setting?

Related

• Wiring Skills Into Loops — feedback loops that improve agent behavior over time
• Claude Code Overview — agent communication patterns