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Solid Ai Templates

AI community

Description

Generate CLAUDE.md and AGENTS.md files from composable, SOLID-inspired templates

Installation

This entry records only its repository, not the path inside it, so there is no exact command to give. Open the source below and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

README

SOLID-AI Templates

*Forged in real work, not theorized — every rule here came from a real AI-assisted project.*

You've shipped the same CLAUDE.md three times this quarter. Each copy is slightly different, none of them are right, and the agent still doesn't know your team's conventions.

You're not alone, and it's not negligence — writing context files from scratch is the quiet cost of every agent-assisted team. Everyone pays it, few teams have a system for it, and the codebase drifts a little further from your standards every sprint.

This repo gives you composable templates that codify your team's conventions once — base rules, stack rules, company rules — and feed them to every agent on every project. Tax paid. Move on.

Back to the work that actually moves the product. The spikes, the design conversations, the reviews that catch bugs instead of churning style nits.

What it does

  • Build CLAUDE.md or AGENTS.md from reusable layers — base, backend/frontend, stack
  • Fork and extend — layer your team's conventions on the base without modifying it
  • Codify industry standards — 12-factor app, OWASP, SOLID, SemVer, conventional commits
  • Assemble templates you need, override if needed or create new ones

How to use

**Prerequisites:** a local coding agent that can read files from your project directory (Claude Code, Cursor, Codex CLI, Windsurf, or similar).

**Output:** a `CLAUDE.md` or `AGENTS.md` file placed at your project root, containing coding conventions tailored to your stack. Works for new projects and refactoring alike — the context file describes how code *should be written*, giving your agent a consistent target whether starting from scratch or improving existing code. Review and adjust the output before adopting it — results vary by model and prompt size.

Try it — clone and point the agent at the templates

*Fastest path. The agent picks the stack on its own — least input from you, most variance in output.*

Clone the repo and tell the a