brain-approve
Approve, reject, or manage pending brain memories. Use: /brain-approve [all|<id>]
Store a persistent rule or convention that will be injected into all future teammates. Use: /brain-remember <text>
$ npx -y skills add Gr122lyBr/claude-teams-brain --skill brain-remember --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/brain-rememberContext preview
The summary Claude sees to decide when to auto-load this skill.
Store a persistent rule or convention that will be injected into all future teammates. Use: /brain-remember <text>
name: brain-remember description: | Store a persistent rule or convention that will be injected into all future teammates. Use: /brain-remember <text> user_invocable: true
Store a fact, rule, or convention in the brain. It will be automatically injected into every future teammate under "Project Rules & Conventions" — regardless of their role.
The user provides the memory text as an argument.
Run:
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/brain_engine.py remember "$ARGS" "$CLAUDE_PROJECT_DIR"Confirm success and echo back the stored memory. Note: memories are now staged as **PENDING**. Use `/brain-approve` to confirm them, or approve via the `/brain-dashboard`. Tell the user it will appear in every new teammate's context once approved. Mention `/brain-forget` to remove it if needed.
Give your Claude Code Agent Teams a memory. Auto-injects role-specific context into every new teammate — your team never starts blind again.
Repo: Gr122lyBr/claude-teams-brain
Approve, reject, or manage pending brain memories. Use: /brain-approve [all|<id>]
Launch the brain dashboard web UI to visualize and curate memories, decisions, and files. Trigger: /brain-dashboard
Export accumulated brain knowledge as a CONVENTIONS.md file in your project. Distills all rules, decisions, files, and agent roles into a committable file.
Remove a manually stored memory from the brain by partial text match. Use: /brain-forget <text>
Export accumulated brain knowledge as `CONVENTIONS.md` and open a GitHub PR so your whole team can review what the AI team learned.