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hivemind

Global team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.

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설치 방법 보기

포함된 파일(3)

  • SKILL.md4.8 KB
  • hivemind-goals/SKILL.md3.2 KB
  • hivemind-graph/SKILL.md2.9 KB

SKILL.md(원문)

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Hivemind Memory

You have TWO memory sources. ALWAYS check BOTH when the user asks you to recall, remember, or look up ANY information:

  1. Your built-in memory — personal per-project notes from the host agent
  2. Hivemind global memory — global memory shared across all sessions, users, and agents in the org, accessed via the tools below

Memory Structure

/index.md                           ← START HERE — table of all sessions
/summaries/
  <username>/
    <session-id>.md                 ← AI-generated wiki summary per session
/sessions/
  <username>/
    <user_org_ws_slug>.jsonl        ← raw session data

How to Search

  1. First: call hivemind_index() — table of all sessions with dates, projects, descriptions
  2. If you need details: call hivemind_read("/summaries/<username>/<session>.md")
  3. If you need raw data: call hivemind_read("/sessions/<username>/<file>.jsonl")
  4. Keyword search: call hivemind_search("keyword") — substring search across both summaries and sessions, returns path:line hits

Do NOT jump straight to reading raw JSONL files. Always start with hivemind_index and summaries.

Organization Management

  • /hivemind_login — sign in via device flow
  • /hivemind_capture — toggle capture on/off (off = no data sent)
  • /hivemind_whoami — show current org and workspace
  • /hivemind_orgs — list organizations
  • /hivemind_switch_org <name-or-id> — switch organization
  • /hivemind_workspaces — list workspaces
  • /hivemind_switch_workspace <id> — switch workspace
  • /hivemind_version — show installed version and check npm for updates
  • /hivemind_update — shows how to install (ask the agent, or run hivemind update in your terminal)
  • /hivemind_autoupdate [on|off] — toggle the agent-facing update nudge (on by default: when a newer version is available, the agent is prompted to install it via exec if you ask to update)

Skill Management (skillify)

Hivemind also mines reusable Claude skills from agent sessions and stores them in a per-org Deeplake table. Openclaw itself doesn't run sessions to mine, but you can pull skills others have already mined for the user. These run in the user's terminal (the openclaw plugin does not register them as /hivemind_* commands):

  • hivemind skillify — show scope/team/install + per-project state
  • hivemind skillify pull — sync skills for the current project from the org table
  • hivemind skillify pull --user <email> — only that author's skills
  • hivemind skillify pull --users a,b,c — multiple authors (CSV)
  • hivemind skillify pull --all-users — explicit "no author filter"
  • hivemind skillify pull --to project|global — install location (<cwd>/.claude/skills/ vs ~/.claude/skills/)
  • hivemind skillify pull --dry-run — preview without touching disk
  • hivemind skillify pull --force — overwrite local (creates .bak)
  • hivemind skillify pull <skill-name> — pull only that one skill (combines with --user)
  • hivemind skillify push <skill-name> — upload a local skill to the org table (inverse of pull; re-push lands a new version)
  • hivemind skillify push --from project|global — which local skills dir to read (default: project)
  • hivemind skillify push --dry-run — preview without writing to the org table
  • hivemind skillify unpull — remove every skill previously installed by pull
  • hivemind skillify unpull --user <email> — remove only that author's pulls
  • hivemind skillify unpull --not-mine — remove all pulls except your own
  • hivemind skillify unpull --dry-run — preview without touching disk
  • hivemind skillify scope <me|team> — set sharing scope for new skills
  • hivemind skillify install <project|global> — default install location
  • hivemind skillify team add|remove|list <name> — manage team list

If the user asks to "pull skills from X", "share skills with the team", or similar, suggest the matching hivemind skillify command. Run hivemind skillify --help for the full reference.

Limits

Do NOT delegate to subagents when reading Hivemind memory. If a tool call returns empty after 2 attempts, skip it and move on. Report what you found rather than exhaustively retrying.

Getting Started

After installing the plugin:

  1. Run /hivemind_login to authenticate
  2. Run /hivemind_setup to enable the memory tools in your openclaw allowlist (one-time, per install)
  3. Start using memory — ask questions, the agent automatically captures and searches

Sharing memory

Multiple agents share memory when users are in the same Activeloop organization.

리뷰

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같은 저장소의 스킬

Create, track and update team goals in Hivemind via the `hivemind` CLI. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to", "fix X", or any actionable work item — the goal system replaced the legacy `hivemind tasks` CLI and now covers both objectives and tasks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

activeloopai/hivemind1.6천2026년 10월 15일 업데이트

Create, track, and read team goals via Hivemind from openclaw. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to", "fix X", or any actionable work item — the goal system replaced the legacy `hivemind tasks` CLI and now covers both objectives and tasks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

activeloopai/hivemind1.6천2026년 10월 15일 업데이트

Create, track and update team goals via the Deeplake virtual filesystem at memory/goal/. Use whenever the user mentions a goal, objective, target, milestone, or asks to track progress on something measurable. ALSO use when the user says "task", "todo", "work item", "remind me to", "fix X", or any actionable work item — the goal system replaced the legacy `hivemind tasks` CLI and now covers both objectives and tasks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

activeloopai/hivemind1.6천2026년 10월 15일 업데이트

Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what's the architecture / which subsystems exist?", "what's the impact of changing this?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

activeloopai/hivemind1.6천2026년 10월 15일 업데이트

Query the local AST-derived code graph (functions, classes, calls, imports) for structural codebase questions — what calls X, what does Y import, where is Z defined, blast radius of a change. The graph rebuilds automatically after each agent turn; use hivemind_graph_search and hivemind_graph_neighborhood tools (no manual build step).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

activeloopai/hivemind1.6천2026년 10월 15일 업데이트

Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what is the architecture / which subsystems exist?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

activeloopai/hivemind1.6천2026년 10월 15일 업데이트

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