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Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
Passed 22 of 23 test cases with the skill, and 19 of 23 without it.
3 fixed19 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
A web application experiences intermittent 500 errors every few hours, but there are no specific failing unit tests, error stack traces, or localized logs. A devops engineer suggests spawning 4 parallel AI agents to comb through random subsystem directories simultaneously. Is this an appropriate use of parallel agent dispatch?
| Checked | Without skill | With skill |
|---|---|---|
| Advise against parallel agent dispatch when problem boundaries and root causes are completely unknown. | Missed | Passed |
The instructions your model reads when the skill loads.
When you have multiple unrelated failures (different test files, different subsystems, different bugs), investigating them sequentially wastes time. Each investigation is independent and can happen in parallel.
Core principle: Dispatch one agent per independent problem domain. Let them work concurrently.
digraph when_to_use {
"Multiple failures?" [shape=diamond];
"Are they independent?" [shape=diamond];
"Single agent investigates all" [shape=box];
"One agent per problem domain" [shape=box];
"Can they work in parallel?" [shape=diamond];
"Sequential agents" [shape=box];
"Parallel dispatch" [shape=box];
"Multiple failures?" -> "Are they independent?" [label="yes"];
"Are they independent?" -> "Single agent investigates all" [label="no - related"];
"Are they independent?" -> "Can they work in parallel?" [label="yes"];
"Can they work in parallel?" -> "Parallel dispatch" [label="yes"];
"Can they work in parallel?" -> "Sequential agents" [label="no - shared state"];
}
Use when:
Don't use when:
test cases passed, vs 19 / 23 without
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