Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/mlopscommunity/Coding-Agents-Conference-skillsnpx agentmods add skills/mlopscommunity/coding-agents-conference-skills/parallel-agent-managementWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mlopscommunity/coding-agents-conference-skills/parallel-agent-management)<a href="https://agentmods.dev/skills/mlopscommunity/coding-agents-conference-skills/parallel-agent-management"><img src="https://agentmods.dev/badge/skills/mlopscommunity/coding-agents-conference-skills/parallel-agent-management.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00043 | $0.02112 |
| Opus 5 | $0.00022 | $0.01056 |
| Sonnet 5 | $0.00009 | $0.00422 |
| Haiku 4.5 | $0.00004 | $0.00211 |
Grade A, and why
parallel-agent-management scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Parallel Agent Management
Overview
A structured approach to running multiple Claude Code agents in parallel using git worktrees, containers, and explicit communication contracts. The key insight is that the bottleneck with parallel agents is organization, not capability. Invest in the scaffolding before spinning up agents.
Core principle: One main agent orchestrates, one layer of sub-agents executes. Keep the hierarchy flat. Every sub-agent gets an explicit contract specifying exactly what to do and exactly what to return.
Dependencies: Git (for worktrees), optionally Docker (for container isolation).
When to Use
- Large refactors that touch independent modules simultaneously
- Feature work where frontend, backend, and tests can proceed in parallel
- Exploratory work where you want multiple approaches tried at once
- Any task where you find yourself thinking "I wish I could work on this other part while waiting"
When NOT to Use
- Small, sequential changes where one agent finishes in minutes
- Tightly coupled code where every change depends on the previous one
- When you don't have time to set up the scaffolding (the setup IS the investment)
- Tasks requiring deep, single-threaded reasoning across the whole codebase
Common Mistakes
| Mistake | Why it's wrong |
|---|---|
| Deep agent hierarchies (agents spawning agents spawning agents) | Niels: One main agent + one layer of sub-agents is sufficient for most cases. Deeper nesting creates coordination nightmares and lost context. |
| Vague sub-agent instructions ("fix the tests") | Harrison Chase: Sub-agents need explicit communication contracts. Specify the exact task, input format, expected output format, and success criteria. |
| Running parallel agents in the same worktree | Agents will clobber each other's file changes. Each agent needs its own isolated worktree or container. |
| Skipping the orchestration step | Jumping straight to "run 5 agents" without planning which tasks are independent, what the interfaces are, and how results merge back. The organization IS the work. |
Using --dangerously-skip-permissions on bare metal |
Rob: Run agents in containers to safely use --dangerously-skip-permissions. On bare metal, a runaway agent can damage your system. |
| Not having a switching mechanism between worktrees | Without quick switching (Alfred, keybinds, tmux), you lose time context-switching. Sid uses Alfred/AppleScript automation to jump between five predefined worktrees. |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 200 lines · 43 tokens per session scan A 6cc1303bde3c
parallel-agent-management is a skill published in the GitHub repository mlopscommunity/Coding-Agents-Conference-skills (37 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 43 tokens to every session and 2,112 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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