[FEATURE] Recognize and Skip Social/Conversational Phrases Without Token Consumption

Preflight Checklist

• [x] I have searched existing requests and this feature hasn't been requested yet
• [x] This is a single feature request (not multiple features)

Problem Statement

Summary

Claude Code burns tokens processing social phrases like "thank you", "ok", "got it", or "sounds good" — phrases that carry no actionable intent. For a paid subscription user, this results in unnecessary API cost and latency for zero productive output.

Current Behavior

When a user types a social acknowledgement such as:

"thank you"

Claude Code sends it through the full inference pipeline, consuming approximately 15 tokens, and responds with a conversational reply — providing no value to the coding session.

Expected Behavior

Claude Code should perform lightweight intent classification before invoking the LLM. Phrases that are purely social or conversational with no actionable coding intent should be:

• Acknowledged with a static/canned response (e.g. "You're welcome! Let me know if you need anything."), or
• Silently skipped with no token consumption at all

Why This Matters

Claude Code is a terminal-based agentic tool — its primary interface is the command line, and its users are developers. However, developers are still humans. Natural social exchanges are a normal part of human-computer interaction, especially with a conversational AI agent.

The current design appears to treat every user input as a potential coding command and routes it through full inference. This is inefficient when:

• The user is on a paid subscription (Pro or API billing)
• The phrase has zero lexical or semantic overlap with any actionable task
• The token cost is entirely wasteful

Environment

• Platform: macOS
• Claude Code version: latest
• Subscription: Claude Pro ($20/month)

Proposed Solution

Add a pre-inference filter or lightweight classifier that:

1. Detects low-information social phrases ("thanks", "thank you", "ok", "great", "cool", "bye", etc.)
2. Responds with a static string or skips the LLM call entirely
3. Logs the skip transparently if debug mode is on

This is a standard optimization in production conversational systems and would meaningfully reduce wasted tokens for users.

Alternative Solutions

_No response_

Priority

High - Significant impact on productivity

Feature Category

Interactive mode (TUI)

Use Case Example

_No response_

Additional Context

_No response_