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Get Started Free →Coordinate multiple agents by splitting work into research, synthesis, implementation, and verification, assigning ownership, and keeping the coordinator focused on integration rather than raw exploration.
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-08 | ✗→✓ | ▲ Improved | -71% | 0% |
| case-10 | ✗→✓ | ▲ Improved | -40% | 0% |
| case-11 | ✗→✓ | ▲ Improved | -78% | 0% |
| case-12 | ✗→✓ | ▲ Improved | 3% | 0% |
| case-16 | ✗→✓ | ▲ Improved | -58% | 0% |
Use this skill when a task is large enough that one coordinator and several bounded workers are more reliable than one monolithic agent loop.
Generate a task-board skeleton:
bashpython3 {baseDir}/scripts/task_board.py --goal "Investigate flaky CI failure" --worker research --worker implementation --worker verification
Then use the coordinator prompt in references/prompt-template.md.
The coordinator should own planning, routing, and synthesis. Workers should own bounded execution.
python3 {baseDir}/scripts/task_board.py ...Other measured skills in the registry, with their headline benchmark lift.