Wikiloop — AI skill for Claude Code

wikiloop

Turn what agents learn while working into reviewed, shared team knowledge.

Every session can make the next one smarter

wikiloop turns useful lessons from agent sessions into reviewed skills, grounded in your team's docs, code, and decisions. Agents start informed by what the team has already learned and propose new knowledge as they work. Each accepted lesson gives future sessions better context for the task ahead.

One shared memory for the whole team

What one agent learns can help everyone. Your team keeps its knowledge in a shared Git repository, and wikiloop distributes it as a plugin for **Claude Code and Codex**. Lessons carry across people, projects, and machines, so the team's knowledge grows with its work.

How it works

The wiki is a collection of **skills**: Markdown instructions that an agent loads when a task calls for them. A skill can explain a product, describe a workflow, record a decision, or guide a recurring task. Detailed context and sources live alongside it in reference files.

1. Use what the team already knows. A session hook tells the agent to load the relevant wiki skill before acting on a subject it covers.
2. Propose what is missing. After work involving tools or skills your team has configured, and once the user has replied, a hook prompts the agent to check for a useful lesson. The agent files a candidate issue explaining the lesson and why it belongs in the wiki, or reports that there is nothing new to add.
3. Review and incorporate it. A maintainer invokes the shepherd workflow to triage candidates, turn accepted lessons into PRs, have a separate agent review them, and merge what passes review and CI. Questions the agents cannot verify go to a person.
4. Keep it useful. Maintainers run source checks to find knowledge that may have changed and trigger evals to check whether real prompts lead agents to the right skills.

For example, an agent learns that two steps in a publis