This is a multi-agent orchestration workflow that breaks down research tasks into parallel subtasks, runs each in a non-interactive Claude Code subprocess with `claude -p`, and assembles the results into a polished report file. It prioritizes installed skills for web operations, falls back to MCP tools like Firecrawl or Exa, and manages everything through a structured `.research/` directory with logs, raw data, and child outputs. The flow is rigorous: it requires upfront scoping with real samples, waits for user confirmation before execution, and enforces chapter-by-chapter refinement rather than wholesale rewrites. Use it for systematic competitive analysis, industry research with dozens of sources, or any investigation that needs coordinated parallel data gathering and a deliverable report rather than chat responses. The 15-minute timeout per subprocess and mandatory progress logging keep long-running jobs observable.
npx -y skills add feiskyer/claude-code-settings --skill deep-research --agent claude-codeInstalls into .claude/skills of the current project.
Select a file.
sickn33/antigravity-awesome-skills
moizibnyousaf/ai-agent-skills
github/awesome-copilot