deep-research workflow spawned 98 agents and consumed 700k+ tokens for a trivial question
Summary
The deep-research skill/workflow was triggered for an extremely simple question: \"How do I set static white RGB on a Razer BlackWidow Chroma V2 at Linux startup without Razer Synapse?\"
The result: 98 agents spawned, 700k+ tokens consumed, before I manually stopped it. The answer was 10 lines of shell commands that Claude already knew without any research.
What happened
- User asked a simple Linux peripheral configuration question.
- Claude invoked the
deep-researchworkflow (via thedeep-researchskill). - The workflow fanned out into 98 parallel agents doing web searches, fetching sources, adversarial verification, synthesis — the full pipeline.
- User noticed the token count and interrupted. Claude cancelled the workflow and answered from existing knowledge in ~10 lines.
Why this is a serious problem
This user is on the Max plan (~€110/month). Token consumption at this scale for a trivial question is not acceptable. The deep-research workflow has no proportionality check — it runs the same heavy pipeline regardless of whether the question is "plan a distributed system from scratch" or "how do I set a keyboard color".
Expected behavior
- The
deep-researchskill should only be invoked when the question genuinely requires multi-source research that Claude cannot answer from training data. - There should be a lightweight path: a simple
WebSearchcall (1-2 searches) for questions that just need a quick fact-check. - The skill description or guardrails should prevent this overkill for questions with well-known, stable answers.
Impact
- Massive unnecessary token burn on a paid Max plan
- Slow response (workflow runs for minutes)
- No added value — the final answer came entirely from Claude's existing knowledge, not from the 98-agent pipeline
Suggestion
Add a complexity/scope gate before launching deep-research. If the question can be answered from training data with reasonable confidence, answer directly or use a single WebSearch. Reserve the full workflow for genuinely complex, multi-faceted research tasks.
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Reported on behalf of a frustrated Max plan user.
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