groundwork
llms.txt0 starsChanged 50 days agoMITView on GitHub
Production-grade NestJS + Next.js monorepo starter: strict TypeScript, Zod contracts shared across apps, Next.js BFF, server-side session auth with TOTP 2FA, BullMQ worker, real-database tests, and first-class rules for AI coding agents. Start with AGENTS.md: it is the canonical rulebook for agents and humans. Each workspace has its own AGENTS.md with local rules.
In this repository15 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- .github/copilot-instructions.mdCopilot instructions
- .cursor/rules/000-project.mdcCursor rule
- .cursor/rules/010-typescript.mdcCursor rule
- .cursor/rules/020-api.mdcCursor rule
- .cursor/rules/030-web.mdcCursor rule
- .cursor/rules/040-database.mdcCursor rule
- .cursor/rules/050-worker.mdcCursor rule
- .cursor/rules/060-testing.mdcCursor rule
- add-endpointSkill
- db-migrationSkill
- new-moduleSkill
- verifySkill
- write-testsSkill
The file
We split this llms.txt into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 5
Start with AGENTS.md: it is the canonical rulebook for agents and humans.
≈ “Common” is an estimate: at least 1 in 5 of the 3,592 llms.txt files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
# Groundwork > Production-grade NestJS + Next.js monorepo starter: strict TypeScript, Zod contracts shared across apps, Next.js BFF, server-side session auth with TOTP 2FA, BullMQ worker, real-database tests, and first-class rules for AI coding agents. Start with AGENTS.md: it is the canonical rulebook for agents and humans. Each workspace has its own AGENTS.md with local rules. ## Rules and workflow - [AGENTS.md](AGENTS.md): conventions, commands, definition of done - [CLAUDE.md](CLAUDE.md): Claude Code skills, subagents, hooks, MCP - [docs/principles.md](docs/principles.md): engineering principles ## Architecture - [docs/architecture/overview.md](docs/architecture/overview.md): components and request flow - [docs/architecture/authentication.md](docs/architecture/authentication.md): sessions, 2FA, tokens - [docs/adr/README.md](docs/adr/README.md): architecture decision records ## Guides - [docs/guides/getting-started.md](docs/guides/getting-started.md) - [docs/guides/adding-a-module.md](docs/guides/adding-a-module.md) - [docs/guides/api-conventions.md](docs/guides/api-conventions.md) - [docs/guides/testing.md](docs/guides/testing.md) - [docs/guides/deployment.md](docs/guides/deployment.md) ## Code entry points - [apps/api/src/app.module.ts](apps/api/src/app.module.ts): API modules - [apps/api/src/modules/auth](apps/api/src/modules/auth): reference implementation of the action pattern - [apps/web/src/lib/api/call.ts](apps/web/src/lib/api/call.ts): typed BFF calls - [packages/shared/src](packages/shared/src): shared contracts - [scripts/gen/templates.mjs](scripts/gen/templates.mjs): what a generated module looks like
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

