Reducing Token Costs in Multi-Agent OpenClaw Pipelines: 6 Proven Strategies

Running multiple agents in OpenClaw can eat through your API credits fast—especially when building content pipelines or orchestrating complex workflows. Here are six battle-tested strategies from the community to keep costs under control while maintaining performance.

1. Use Cheaper Models for Sub-Agents

Your main chat agent needs to be responsive and smart, but background sub-agents doing grunt work? They can run on cheaper models.

Configure this with:

agents:
  defaults:
    subagents:
      model: openrouter/google/gemini-flash-1.5

This reduces token costs for background tasks while keeping your main chat responsive. The key insight: not every agent needs your most expensive model.

2. Optimize Bootstrap and Workspace Content

Every time an agent starts a session, it loads your workspace files (SOUL.md, MEMORY.md, etc.). If these are bloated, you're burning tokens before any real work happens.

Limit the damage with:

agents:
  defaults:
    bootstrapMaxChars: 10000
    bootstrapTotalMaxChars: 25000

Keep your bootstrap files lean. Move historical context to memory files that get searched rather than injected wholesale.

3. Prune Old Sessions Regularly

Old session files pile up in ~/.openclaw/agents/<agentId>/sessions/. They don't just take up disk space—they can slow down session restoration and waste resources.

Clean them out:

# See what you have
ls -la ~/.openclaw/agents/main/sessions/ | wc -l

# Remove sessions older than 7 days
find ~/.openclaw/agents/*/sessions -type f -mtime +7 -delete

4. Run Heavy Tasks in Sub-Agents

Don't clog your main agent with long-running tasks. Spawn sub-agents for:

• File processing
• Web scraping batches
• Code analysis
• Research tasks

Sub-agents keep your main chat responsive and can be killed/pruned when done.

5. One Active Workspace Per Agent

Running the same agent across multiple workspaces creates duplicate context loading and session overhead. Stick to a single active workspace per agent to reduce token waste.

Use openclaw doctor to identify stray workspaces:

openclaw doctor

This will flag profile mismatches and orphaned workspaces you can clean up.

6. Monitor Token Usage

OpenClaw tracks tokens, not characters. A seemingly short message with code blocks or structured data can burn way more tokens than plain text.

Watch your usage:

/status  # In chat, shows session token usage
openclaw status --verbose  # CLI, shows provider-level usage

The Bottom Line

Multi-agent setups multiply your model usage. The formula is simple:

More agents × Longer sessions × Bigger context = Higher costs

But you don't have to sacrifice capability. Smart model selection, lean bootstrap configs, and regular maintenance let you run sophisticated pipelines without the credit card panic.

From the OpenClaw Discord, originally shared by community member Val 🦞. These tips have helped multiple users cut their API costs by 40-60% while running content pipelines.