Coordinate parallel scientist agents for multi-stage research workflows.
npx skills add https://github.com/INNERJOINT/HarnessSkills --skill sciomc-innerjoint
Please help me install this Agent Skill. Skill: sciomc Source: https://github.com/INNERJOINT/HarnessSkills/tree/main/skills/sciomc Command: npx skills add https://github.com/INNERJOINT/HarnessSkills --skill sciomc-innerjoint
Orchestrate parallel scientist agents for comprehensive research goals, coordinating stages, analyses, and synthesis with AUTO mode to reduce manual overhead.
Provide a research goal and start an autonomous sciomc session to decompose, run, verify, and synthesize results.
High-intent search queries and answers about installing and using this skill.
Multi-agent research orchestration is automated by decomposing complex goals into independent stages, running parallel scientist agents, and using AUTO mode to execute tasks autonomously until completion with progress tracking.
AUTO mode in parallel AI agent execution enables fully autonomous operation across complex goals, managing multi-stage decomposition, cross-stage verification, and progress state until a unified research report is synthesized.
To analyze a codebase for security patterns, you provide a research goal to start an autonomous session, which decomposes the task and runs concurrent agents to produce a comprehensive security assessment.
Cross-validating findings from multiple AI agents is supported through explicit cross-stage verification, ensuring that results generated by parallel scientist agents are checked before final result synthesis and reporting.
Autonomous research orchestration does not require manual intervention between stages, as it enforces deterministic task models, explicit stage routing, and AUTO mode to manage progress state and synthesis independently.
Deterministic task models for parallel agent orchestration limit execution flexibility by enforcing explicit stage routing and structured sessions, requiring goals to be decomposable into independent stages for successful parallel processing.
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