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Get Started Free →Design a small team of AI agents to tackle a complex task in parallel — who does what, how they hand off, and how to keep them coordinated — instead of one overloaded agent doing everything serially. Use when asked how do I use multiple AI agents, set up an agent team, orchestrate agents for, or run agents in parallel. Produces a decomposition of the task into agent roles, a coordination pattern (parallel vs sequential, how outputs combine), the context each agent needs (and what to keep isolate
.claude/skills/mohitagw15856-run-an-agent-team/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-06 | ✗→✓ | ▲ Improved | -24% | 0% |
| case-01 | ✗→✓ | ▲ Improved | -16% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 44% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 14% | 0% |
| case-10 | ✗→✓ | ▲ Improved | -53% | 0% |
Complex tasks overwhelm a single AI agent — the context gets muddy, quality drops, and it does everything serially. A small team of specialized agents, each with a focused role and clean context, can tackle it in parallel and check each other's work. This designs that team for your task: the roles, how they coordinate and hand off, what context each needs (and what to isolate), and the guardrails — turning "one agent doing everything" into a coordinated effort.
Ask for these if not provided:
Needs a team? yes — parts are parallel/benefit from isolation / no — one agent is better because Z]. Roles | Agent | Responsibility | Context it needs / isolate | |---|---|---| | researcher] | | | | builder] | | | | critic] | | | | integrator] | | |
Coordination: parallel / sequential / mix] — outputs combine by how]. Review pass: critic/integrator checks & merges]. Guardrails: clear objectives · defined outputs · iteration limit · human checkpoint.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-06 | fail→pass | 29,244 | 18,867 | -35% | 1 | 1 | 0% | 4,263 | 3,250 | -24% | 0 | 0 | — |
case-01 | fail→pass | 36,422 | 25,682 | -29% | 1 | 1 | 0% | 5,359 | 4,522 | -16% | 0 | 0 | — |
case-02 | fail→fail | 40,363 | 19,923 | -51% | 1 | 1 | 0% | 6,111 | 4,347 | -29% | 0 | 0 | — |
case-03 | fail→fail | 37,321 | 23,660 | -37% | 1 | 1 | 0% | 6,678 | 4,085 | -39% | 0 | 0 | — |
case-04 | fail→pass | 9,508 | 13,700 | +44% | 1 | 1 | 0% | 1,679 | 2,424 | +44% | 0 | 0 | — |
case-05 | fail→fail | 56,179 | 29,623 | -47% | 1 | 1 | 0% | 8,238 | 4,484 | -46% | 0 | 0 | — |
case-07 | fail→fail | 39,088 | 23,646 | -40% | 1 | 1 | 0% | 5,933 | 3,978 | -33% | 0 | 0 | — |
case-08 | fail→fail | 30,489 | 26,564 | -13% | 1 | 1 | 0% | 4,488 | 4,072 | -9% | 0 | 0 | — |
case-09 | fail→pass | 21,046 | 40,924 | +94% | 1 | 1 | 0% | 3,741 | 4,249 | +14% | 0 | 0 | — |
case-10 | fail→pass | 61,577 | 21,812 | -65% | 1 | 1 | 0% | 7,897 | 3,733 | -53% | 0 | 0 | — |
case-11 | pass→pass | 17,674 | 16,134 | -9% | 1 | 1 | 0% | 1,790 | 3,004 | +68% | 0 | 0 | — |
case-17 | pass→fail | 20,228 | 18,288 | -10% | 1 | 1 | 0% | 2,177 | 3,555 | +63% | 0 | 0 | — |
case-12 | fail→fail | 47,781 | 21,784 | -54% | 1 | 1 | 0% | 5,934 | 4,861 | -18% | 0 | 0 | — |
case-13 | fail→pass | 32,760 | 18,773 | -43% | 1 | 1 | 0% | 3,991 | 4,535 | +14% | 0 | 0 | — |
case-14 | fail→fail | 39,803 | 23,209 | -42% | 1 | 1 | 0% | 6,056 | 4,155 | -31% | 0 | 0 | — |
case-15 | pass→fail | 22,643 | 23,713 | +5% | 1 | 1 | 0% | 3,124 | 4,301 | +38% | 0 | 0 | — |
case-16 | pass→fail | 14,908 | 14,401 | -3% | 1 | 1 | 0% | 1,423 | 3,595 | +153% | 0 | 0 | — |
case-18 | fail→pass | 36,588 | 28,098 | -23% | 1 | 1 | 0% | 6,781 | 4,742 | -30% | 0 | 0 | — |
case-19 | fail→pass | 23,088 | 16,099 | -30% | 1 | 1 | 0% | 3,558 | 3,533 | -1% | 0 | 0 | — |
case-20 | fail→pass | 31,559 | 21,087 | -33% | 1 | 1 | 0% | 4,388 | 4,306 | -2% | 0 | 0 | — |
case-21 | fail→pass | 27,690 | 21,051 | -24% | 1 | 1 | 0% | 4,741 | 4,404 | -7% | 0 | 0 | — |
case-22 | fail→fail | 30,133 | 17,200 | -43% | 1 | 1 | 0% | 4,428 | 3,926 | -11% | 0 | 0 | — |
case-23 | fail→pass | 22,664 | 24,563 | +8% | 1 | 1 | 0% | 2,534 | 3,469 | +37% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted. The headline lift of +35 percentage points is the difference between those two pass rates over the 23 comparable cases. 3 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.