Other agents
Claude Code, OpenCode, and Cursor get plug-and-play install. Other agents need a one-time copy-paste because they don’t have a skills directory.
The pattern is the same everywhere:
- Copy the contents of
dig/SKILL.mdinto your agent’s long-lived instruction file (AGENTS.md,~/.aider.conf.yml, system prompt, etc.). - Tell the agent “follow the dig skill” or “do an excavation pass” — the skill instructions do the rest.
Codex CLI
Section titled “Codex CLI”Codex reads AGENTS.md from the repo root and from ~/.codex/AGENTS.md.
mkdir -p ~/.codexcat ~/.local/share/indiana-codes/dig/SKILL.md >> ~/.codex/AGENTS.mdOr, if you’d rather not pollute every conversation, paste it inline when you want to dig:
Follow these instructions to excavate this codebase:
<paste contents of dig/SKILL.md>Aider supports a config-level read: list for files always loaded into context.
read: - ~/.local/share/indiana-codes/dig/SKILL.mdStart aider and say “follow the dig skill”.
Continue.dev
Section titled “Continue.dev”Add a custom slash command in ~/.continue/config.yaml:
customCommands: - name: dig description: Code archaeology — chapter-based history walkthrough prompt: | <paste contents of dig/SKILL.md>Zed AI
Section titled “Zed AI”Drop the contents into a .rules file at the repo root, or paste into the assistant panel as a system message. Zed honours .rules automatically when its assistant runs.
Generic / any chat-style assistant
Section titled “Generic / any chat-style assistant”The skill is self-contained. Paste dig/SKILL.md into the system prompt of whatever assistant you’re using and say “begin Phase 1.” Works in raw Claude / GPT / Gemini chat windows too — you just lose the slash-command ergonomics and have to run git commands yourself when the assistant asks for output.
A note on tool access
Section titled “A note on tool access”Code Archaeology gets much better when the agent can call git, gh, and any issue-tracker MCPs you have configured. Agents that can’t shell out (most chat sandboxes) will stall at Phase 1 — you’ll have to be the hands-and-feet, pasting command output back to the model. Workable, but slow. Prefer an agent with shell access if you have the choice.