Orchestrate parallel scientist agents to verify and synthesize research reports.
npx skills add https://github.com/xdkp/oh-my-claudecode --skill sciomc-xdkp
Please help me install this Agent Skill. Skill: sciomc Source: https://github.com/xdkp/oh-my-claudecode/tree/main/skills/sciomc Command: npx skills add https://github.com/xdkp/oh-my-claudecode --skill sciomc-xdkp
sciomc eliminates slow, single-threaded research by orchestrating multiple “scientist” agents in parallel, then verifying and synthesizing their results into a comprehensive report with optional fully autonomous execution.
Use Cases: security analysis across components, architecture and dependency understanding, performance-characteristics research, and any investigation that benefits from independent sub-questions plus reconciliation.
Run: /oh-my-claudecode:sciomc AUTO: Analyze the error-handling and authentication flow across this codebase and produce a consolidated report.
High-intent search queries and answers about installing and using this skill.
Parallel research analysis decomposes a complex goal into independent hypotheses, concurrently executes scientist agents on different file areas, and cross-validates results to generate a synthesized report. You can trigger this workflow using the AUTO mode command with your specific research goal.
Automated multi-stage codebase investigation uses an AUTO mode loop to handle decomposition, parallel execution, verification, and synthesis autonomously. The system emits promise tags until the task completes or blocks, preserving session state to support resuming if interrupted.
Yes, you can resume a parallel research session because the system persists session state across iterations. It supports status checks, resume, list, report generation, and cancellation commands to manage concurrency limits and stable execution.
Cross-validation during synthesis detects contradictions, coverage gaps, and evidence quality issues across concurrent agent outputs. This verification loop produces either verified outcomes or conflict-labeled results, ensuring the final report reconciles independent sub-questions accurately.
Yes, explicit model routing for subagent tasks is required during parallel codebase analysis to ensure stable execution. The system applies concurrency limits and requires you to define how independent stages are assigned to specific scientist agents.
Security analysis across components, architecture understanding, dependency mapping, and performance-characteristics research benefit from concurrent execution. Any investigation that can be split into independent sub-questions plus reconciliation is suitable for this parallel scientist approach.
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