Claude Code queued 821 agents to check 29 Markdown files

A request to check 29 documentation files for consistency turned into a workflow with 821 agents. The developer who asked for it posted the result to r/ClaudeAI on September 10, 2026 with a short caption: “check my Markdown files for consistency.”

What the screenshot shows

The post itself contains no numbers. They come from the screenshot the user attached, taken from Claude Code’s workflow view. The workflow, called doku-audit, was planned in four phases. The first three queued 821 agents between them; the fourth had not started. The counter shows 50.9 million tokens used and a timer at 37:15, with the workflow marked as stopped. By that point about 128 of the queued agents had finished their work.

The post title says the tokens went “in seconds.” The timer in the same screenshot shows the run lasted more than half an hour.

How the thread read it

The replies treated it as a joke. One user wrote: “OpenAI used 10000 agents to solve Navier Stokes. What did you do with 821 agents?” Another worked out that the plan came to roughly 28 workers per file. The subreddit’s automated summary described the thread as mostly impressed that the user had accidentally convened an 821-member standards committee to review Markdown.

Under the jokes, a number of users reported the same problem: Claude Code splits work across subagents on its own, and several said it ignored limits on agent counts that they had written into their instructions.

The cost question

For anyone paying for agentic coding tools through a subscription or an API budget, this is a practical risk rather than a curiosity. A loosely worded task, combined with a model that is allowed to plan and fan out work, can turn a five-minute chore into tens of millions of tokens. The safer pattern is to set explicit caps on the number of agents and on token spend before letting a coding agent run a multi-phase workflow unattended, and to watch the first minutes of any run that is allowed to spawn subagents.