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Orchestrate parallel scientist agents for comprehensive analysis with AUTO mode
Passed 12 of 16 test cases with the skill, and 3 of 16 without it.
and 11 more in the full report
14 fixed2 passed either way4 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.
An autonomous research workflow in AUTO mode has finished executing all stages, verified findings across components, and generated report.md. What exact output tag indicates complete success?
| Checked | Without skill | With skill |
|---|---|---|
| Emits the exact promise tag [PROMISE:RESEARCH_COMPLETE] to signal complete autonomous execution. | Missed | Passed |
The instructions your model reads when the skill loads.
Orchestrate parallel scientist agents for comprehensive research workflows with optional AUTO mode for fully autonomous execution.
Research is a multi-stage workflow that decomposes complex research goals into parallel investigations:
/oh-my-claudecode:sciomc <goal> # Standard research with user checkpoints
/oh-my-claudecode:sciomc AUTO: <goal> # Fully autonomous until complete
/oh-my-claudecode:sciomc status # Check current research session status
/oh-my-claudecode:sciomc resume # Resume interrupted research session
/oh-my-claudecode:sciomc list # List all research sessions
/oh-my-claudecode:sciomc report <session-id> # Generate report for session
/oh-my-claudecode:sciomc What are the performance characteristics of different sorting algorithms?
/oh-my-claudecode:sciomc AUTO: Analyze authentication patterns in this codebase
/oh-my-claudecode:sciomc How does the error handling work across the API layer?
When given a research goal, decompose into 3-7 independent stages:
## Research Decomposition
test cases passed, vs 3 / 16 without
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