Compaction triggers too late when calling multiple agents - causes context overflow

Resolved 💬 3 comments Opened Nov 8, 2025 by MRIHub Closed Nov 12, 2025

Problem

Claude Code's compaction system triggers reactively when context is already near/at limit, rather than proactively at a safe threshold. This causes frequent context overflow errors when multiple agents are invoked.

Current Behavior

  • Compaction triggers at ~98-99% context usage
  • Multiple agent calls rapidly consume context (each agent can add 10-20k tokens)
  • Context exceeds limit before compaction completes
  • User sees: Error during compaction: Conversation too long

Expected Behavior

  • Compaction should trigger proactively at 80-85% context usage
  • Block new agent launches when context > 85% until compaction completes
  • Warn user at 75% context with suggestion to compact manually

Reproduction

  1. Start a conversation with moderate context (60-70%)
  2. Launch multiple agents in parallel using Task tool
  3. Context rapidly fills to 100%
  4. Compaction fails with 'Conversation too long' error

Suggested Fix

typescript
// Proactive compaction thresholds
const COMPACT_TRIGGER_THRESHOLD = 0.85; // 85%
const AGENT_BLOCK_THRESHOLD = 0.90; // 90%
const CRITICAL_THRESHOLD = 0.95; // 95%

// Before launching agents
if (contextUsage > AGENT_BLOCK_THRESHOLD) {
triggerCompaction();
blockAgentLaunch();
}

// Background monitoring
setInterval(() => {
if (contextUsage > COMPACT_TRIGGER_THRESHOLD) {
triggerCompaction();
}
}, 1000);

Workarounds

Until fixed, users can:

  1. Manually run /compact before launching multiple agents
  2. Use MCP knowledge-manager to store intermediate results externally
  3. Run agents sequentially with compaction between each

Environment

  • Claude Code version: Latest (as of 2025-11-08)
  • Platform: Linux
  • Typical context usage: High (multi-agent workflows)

Impact

  • Severity: High - blocks common multi-agent workflows
  • Frequency: Every session with 2+ parallel agent calls
  • User Experience: Frustrating, requires manual intervention

Priority

This affects core functionality (multi-agent orchestration) and should be prioritized for the next release.

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