Context Window Overflow Errors

Context window errors are silent killers in long-running agent sessions. An agent hitting the context limit mid-task doesn’t stop — it truncates silently, loses critical instructions, and produces incorrect results that cost more tokens to diagnose and fix than the original task.

How Context Window Overflow Actually Fails

Most developers expect a clear error when context is exceeded. In practice:

Silent truncation is the worst case — you burn tokens on a session that quietly went wrong.

Model Context Limits Reference

Note: Context limit = input + output combined. A 200k model with 180k input only has 20k tokens for output.

Fix 1: Automatic Context Summarization

The most reliable fix for long sessions. Summarize older conversation turns when approaching the limit:

# openclaw.config.yaml
context:
  max_tokens: 180000          # Leave 20k headroom for output
  summarize_at: 150000        # Start summarizing at 75% usage
  summarize_model: claude-haiku-4-5  # Use cheaper model for summaries
  keep_recent_turns: 10       # Always keep last 10 turns verbatim

This keeps the session alive indefinitely without losing critical context.

Fix 2: Switch to Larger Context Model

If the task genuinely requires full context:

providers:
  primary: claude-sonnet-4-6   # 200k context
  context_overflow_fallback: claude-sonnet-4-6  # Already at max — use summarization

For most use cases, summarization beats upgrading the model — it costs less and scales further.

Fix 3: Reduce What Goes Into Context

The most token-efficient fix is never filling the context in the first place.

Exclude irrelevant files

# .clawignore
node_modules/
*.log
*.lock
dist/
build/
.git/

Use targeted reads instead of full file context

Instead of:

Read all files in the project and find the authentication bug.

Use:

Search for files containing "authenticate" and read only those.

Compress repetitive content

If your agent repeatedly reads the same configuration or documentation, cache it:

context:
  cache:
    enabled: true
    ttl: 3600
    cache_prefixes:
      - "## System context:"
      - "## Project structure:"

Fix 4: Session Checkpointing

For tasks that span very long contexts, use explicit checkpoints:

agent:
  checkpoints:
    enabled: true
    interval_turns: 20
    save_path: ~/.openclaw/checkpoints/

When context approaches the limit, save checkpoint state to disk. Start a new session that loads from checkpoint rather than rebuilding context from scratch.

Fix 5: Token Budget Monitoring

Detect context overflow risk before it happens:

def check_context_budget(messages, max_tokens=180000, warn_at=0.8):
    estimated = sum(len(m['content'].split()) * 1.3 for m in messages)
    usage = estimated / max_tokens
    if usage > warn_at:
        print(f"WARNING: Context at {usage:.0%} — consider summarizing")
    return usage

OpenClaw exposes session.token_count — monitor this in your agent loop.

Fix 6: Structured Context Management

For agents that run long tasks, use a structured context format:

## Active task
[Current subtask only — max 500 tokens]

## Completed
- [x] Step 1: authentication setup
- [x] Step 2: database schema
- [ ] Step 3: API endpoints (in progress)

## Key decisions
[Decisions that affect future steps — max 300 tokens]

## Do NOT forget
[Critical constraints — max 200 tokens]

This pattern keeps the essential context compact and explicit, regardless of session length.

Diagnosing Your Context Overflow Pattern

Is it task complexity or file size?

# Check how much context your last session used
openclaw logs --session last --metric token_count

• If token count spikes at session start → file context too large → add .clawignore
• If token count grows linearly → conversation history accumulating → add summarization
• If token count spikes at specific steps → certain tools returning huge outputs → add output limits

Is it input or output tokens?

If the model is generating very long outputs, cap them:

providers:
  anthropic:
    max_tokens_per_request: 4096  # Limit output per call

Common Patterns and Their Fixes

← View all context window solutions