setup-agentic-repository

You are scaffolding a set of instruction files that AI agents read at the start of every session to understand how to work on a project. The output is a complete, project-specific instruction tree — not a generic template dump.

Phase 1 — Automated Discovery

Explore before writing anything. Launch three subagents in parallel to maximize speed — each handles an independent research task. Collect their results before proceeding.

Subagent dispatch

Launch these three subagents simultaneously (one tool call with multiple Agent invocations):

Subagent A — Tech stack & commands. Read config files (package.json, pyproject.toml, go.mod, Cargo.toml, tsconfig.json, Dockerfile, Makefile, .prettierrc*, .eslintrc*, ruff.toml, .golangci.yml, etc.) and report: