repo-scaffold
Scaffold or standardize a production-ready repository structure with specs, source layout, tests, CI, agent context, config examples, release notes, and operational docs. Use when starting a new repo, turning a prototype into a maintainable project, adding missing repository foundations, or creating a repo skeleton before implementation. For AGENTS.md-only context scaffolding, use agentsmd-scaffold.
Works with
--- name: repo-scaffold description: Scaffold or standardize a production-ready repository structure with specs, source layout, tests, CI, agent context, config examples, release notes, and operational docs. Use when starting a new repo, turning a prototype into a maintainable project, adding missing repository foundations, or creating a repo skeleton before implementation. For AGENTS.md-only context scaffolding, use agentsmd-scaffold. license: MIT --- # Repo Scaffold ## Purpose Use this skill to create the repo foundation that lets product, architecture, implementation, verification, and operations stay connected. It is broader than `agentsmd-scaffold`; it may include AGENTS.md, but also specs, tests, CI, config, release, and runbook structure. ## Search First Before adding files, inspect the repo for existing equivalents: ```bash rg --files -g 'AGENTS.md' -g 'CONTRIBUTING.md' -g 'README*' -g 'pyproject.toml' -g 'package.json' -g 'go.mod' -g 'Cargo.toml' -g '.github/workflows/*' -g 'docs/**' -g 'specs/**' -g 'tests/**' ``` Reuse existing conventions. Do not create parallel `docs/`, `spec/`, `planning/`, or `test/` trees when the repo already has a standard location. ## Scaffold Layers Add only the layers needed for the repo: | Layer | Typical Files | |---|---| | Product and specs | `specs/PRODUCT.md`, `specs/TECH.md`, `docs/adr/` | | Agent context | `AGENTS.md`, scoped `AGENTS.md`, local skill notes | | Source layout | language-specific `src/`, `pkg/`, `cmd/`, `app/`, `lib/` | | Tests | `tests/`, fixtures, golden snapshots, e2e harness | | CI | `.github/workflows/ci.yml`, lint/typecheck/test jobs | | Config | `.env.example`, config schema, secret inventory | | Release | `CHANGELOG.md`, release checklist, versioning notes | | Operations | `docs/runbooks/`, SLO and incident templates | ## Decision Rules - For a new repo, propose the tree first, then create files only after the user asks to apply. - For an existing repo, make the smallest additive change that closes the foundation gap. - Keep generated starter files short and executable. Prefer empty placeholders only when a tool requires them. - Do not hardcode credentials, service names, ports, or cloud providers without repo evidence. - Do not overwrite existing README, CI, or config files without showing the diff intent. ## Minimal Output For planning: ```text existing_foundation: missing_layers: proposed_tree: files_to_create_or_update: verification_commands: ``` For implementation, finish by running the repo's validation command and, when available, the scaffold-specific lint or generated-file check.
More Writing & Documentation skills
paper-context-resolver
lllllllama/rigorpilot-skills
Rigor Paper Context helper for README-first deep learning repo reproduction. Use only when the README and repository files leave a narrow reproduction-critical gap and the task is to resolve a specific paper detail such as dataset split, preprocessing, evaluation protocol, checkpoint mapping, or runtime assumption from primary paper sources while recording conflicts. Do not use for general paper summary, repo scanning, environment setup, command execution, title-only paper lookup, or replacing README guidance by default.
repo-intake-and-plan
lllllllama/rigorpilot-skills
Rigor Intake helper for README-first deep learning repo reproduction. Use when the task is specifically to scan a repository, read the README and common project files, extract documented commands, classify inference, evaluation, and training candidates, and return the smallest trustworthy reproduction plan to the main orchestrator. Do not use for environment setup, asset download, command execution, final reporting, paper lookup, or end-to-end orchestration.
minimal-run-and-audit
lllllllama/rigorpilot-skills
Rigor Run skill for README-first deep learning repo reproduction. Use when the task is specifically to capture or normalize evidence from the selected smoke test or documented inference or evaluation command and write standardized `repro_outputs/` files, including patch notes when repository files changed. Do not use for training execution, initial repo intake, generic environment setup, paper lookup, target selection, hidden scientific-meaning changes, or end-to-end orchestration by itself.

