Parallel Sub-Agents in Claude Code: When They Save vs. Burn Tokens

Anthropic numbers often ignored in the "use sub-agents!" hype: multi-agent systems consume about 15× more tokens than a single chat, and they are "less effective for tightly interdependent tasks such as coding" (source). However, cached tokens cost only 10% of normal (90% discount) — but only if the content flagged for caching is identical across requests (source).
Multi-agent multiplies token use by 15. The cache divides it by 10. Whether sub-agents save or burn comes down to one thing: do all sub-agents share the same prefix?
Three Ways to Delegate, Ordered by Cost
- 1. Sub-agent with
subagent_typeset. Custom system prompt, custom tools, custom permissions (Anthropic). Different prompt = different cache. No sharing with the parent. Full price every spawn. Use when you actually need isolation. - 2. Clone that inherits the parent. No
subagent_type. Inherits the parent's prompt, tools, and history exactly. Children 2..N hit the cache at 10% price. Five clones reading files in parallel ≈ 5× speed at ~1.5× cost. - 3. No sub-agent. Stay in the main agent. Cheapest per turn. Right answer when the work depends on itself — refactors where step 2 needs step 1's result.
When NOT to Delegate (Anthropic's Own Line)
"Best for tasks that can be divided into parallel strands of research." Translation:
- Good: read 7 files in parallel, audit folders for a pattern, gather info from many sources.
- Bad: refactor a module, fix a bug where each step depends on the previous. Main agent only.
If you slice tightly coupled work into sub-agents, you pay 15× and gain nothing.
What Breaks the Cache
Anthropic: editing tool definitions, switching models, adding or removing images, or changing the earlier prompt structure breaks the cached prefix (source). So:
- Install your MCPs at session start, not mid-session.
- Pick the model up front.
- Don't edit
CLAUDE.mdor auto-memory mid-session — they live inside the cached prefix.
📖 Read the full source: r/ClaudeAI
👀 See Also

OpenClaw Context Meter Plugin Shows Telegram Token Usage Percentage
A new OpenClaw plugin displays token usage percentage after every Telegram bot response, showing values like '45k / 200k (22%)' and detecting compaction events. The plugin avoids OOM issues by hardcoding context windows instead of using execSync.

Clawdwatch: Open-source OSINT tool for real-time flight tracking, news scraping, and alerts
Clawdwatch is a CLI tool that pulls live flight data from OpenSky Network, scrapes news from Al Jazeera and AP, and can send Telegram alerts for military aircraft or emergency squawks. It runs locally with npm install and tracks 204+ flights over the Middle East in real-time.

Claude Cowork mode explained: file-level task execution vs chat and code modes
Claude's Cowork mode operates inside a chosen folder to perform file-level tasks like organizing messy folders, extracting structured data from screenshots, and combining scattered notes into structured documents.

Claude Code Session Dashboard: Open Source Tool for Monitoring Multiple Sessions
An open-source dashboard that monitors multiple Claude Code sessions simultaneously, showing token usage, costs, session status, context window usage, and active subagents. Installation requires three commands: git clone, cd, and npm install && npm start.