Coordinate multi-agent parallel research with structured phases and consensus reporting.
npx skills add https://github.com/nshonda/workstation-setup --skill research-nshonda
Please help me install this Agent Skill. Skill: research Source: https://github.com/nshonda/workstation-setup/tree/main/claude/skills/research Command: npx skills add https://github.com/nshonda/workstation-setup --skill research-nshonda
Orchestrates deep, parallel research to answer complex codebase questions, architecture decisions, or implementation strategies by coordinating multiple exploratory agents and synthesizing consensus findings.
Provide your task and let the system initiate a multi-agent research run.
High-intent search queries and answers about installing and using this skill.
Multi-agent codebase analysis coordinates parallel exploration agents that investigate your architecture questions, generate phase reports, and synthesize consensus-based recommendations for complex implementation strategies.
Consensus-based codebase research deploys multiple parallel agents to explore a task, then synthesizes their findings into a unified report. You need it for deep architecture decisions or implementation approaches requiring thorough investigation.
To start parallel research, provide your codebase task or question. The system initiates a multi-agent run with structured phases including exploration, documentation, and final consensus reporting with designated artifacts.
Yes, multi-agent research applies to implementation strategies on large codebases by running parallel exploratory agents that investigate different aspects simultaneously and produce consensus findings with structured artifacts.
Multi-agent consensus research coordinates several parallel agents across structured phases to produce synthesized recommendations, whereas standard search returns direct matches without deep investigation or consensus-based reporting.
Multi-agent parallel research is not suited for simple codebase lookups or single-file questions that require no deep investigation, as the structured exploration phases and consensus workflow add overhead better reserved for complex architecture decisions.
fredericpoitevinAsk clarifying questions to define research goals and scope before starting.
ZhanlinCuiDispatch parallel agents to investigate independent failures and aggregate findings.
JayKim88Analyze a codebase to produce a prioritized multi-agent project health report.
MadAppGangCoordinate parallel multi-agent code analyses by sharing claudemem outputs across sessions.
