A skill that scaffolds the LLM Wiki pattern into any project — a persistent, compounding knowledge base that AI agents build and maintain themselves.
Agents start every session with no memory of the last one, so the same context gets rediscovered repeatedly: why a module is structured a certain way, which approach was already tried and rejected, what a bug actually turned out to be. The LLM Wiki pattern fixes this by giving the project a wiki/ directory that agents read before making decisions and update after learning something.
Trigger this skill when the user:
wiki/
├── index.md # Entry point — agents read this first
├── log.md # Append-only record of what was learned and when
├── architecture/ # How the system is put together, and why
├── decisions/ # Choices made, alternatives rejected, rationale
└── concepts/ # Domain terms and project-specific ideas
It also adds the instruction block that tells agents to read wiki/index.md before architectural decisions and to update the relevant page plus wiki/log.md whenever they learn something durable.
The value is in the write path, not the read path. A wiki that agents only read goes stale within weeks. The pattern works because updating it is part of the agent’s normal workflow, so the knowledge base grows as a side effect of doing the work rather than as a separate documentation chore.
ask copy claude --skill ask-wiki-init
Supported agents: Claude Code, Codex, Gemini CLI, Cursor, Antigravity.
ask-project-memory — records architectural decisions and stack choicesask-adr-logger — writes formal Architectural Decision Records