Orchestrate parallel scientist-agent research stages into a verified synthesized report.
npx skills add https://github.com/nichobbs/lyric-lang --skill sciomc-nichobbs
Please help me install this Agent Skill. Skill: sciomc Source: https://github.com/nichobbs/lyric-lang/tree/main/.claude/skills/sciomc Command: npx skills add https://github.com/nichobbs/lyric-lang --skill sciomc-nichobbs
It coordinates complex research by splitting a goal into multiple stages, running them in parallel, validating the results, and synthesizing a single coherent report.
Run /oh-my-claudecode:sciomc <your research goal> to automatically decompose the goal, execute staged parallel investigation, verify findings, and synthesize a final report.
High-intent search queries and answers about installing and using this skill.
To verify conflicting findings from parallel research agents, a cross-validation loop checks stage results for contradictions or missing coverage, producing either a verified outcome or identified conflicts to resolve before final synthesis.
To verify conflicting findings from parallel research agents, a cross-validation loop checks stage results for contradictions or missing coverage, producing either a verified outcome or identified conflicts to resolve before final synthesis.
To verify conflicting findings from parallel research agents, a cross-validation loop checks stage results for contradictions or missing coverage, producing either a verified outcome or identified conflicts to resolve before final synthesis.
To verify conflicting findings from parallel research agents, a cross-validation loop checks stage results for contradictions or missing coverage, producing either a verified outcome or identified conflicts to resolve before final synthesis.
To verify conflicting findings from parallel research agents, a cross-validation loop checks stage results for contradictions or missing coverage, producing either a verified outcome or identified conflicts to resolve before final synthesis.
To verify conflicting findings from parallel research agents, a cross-validation loop checks stage results for contradictions or missing coverage, producing either a verified outcome or identified conflicts to resolve before final synthesis.
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