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hivemind-goals

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.

中文简介正在准备中。当前显示原文说明。

查看安装方法

包含的文件(1)

  • SKILL.md3.2 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Hivemind Goals (openclaw)

OpenClaw exposes purpose-built tools for goals. Use them directly — do NOT try to write files via the host filesystem.

Tools

  • hivemind_goal_add({ text }) — create a new goal. Returns goal_id (UUID). Status starts at opened.
  • hivemind_search({ query }) — search Hivemind shared memory (summaries + sessions). Use this when the user asks "what's already there" before creating a duplicate.
  • hivemind_read({ path }) — read the full content of a specific Hivemind path.
  • hivemind_index({}) — list everything in memory.

Workflow when the user expresses a goal

  1. (Optional) hivemind_search first to surface any existing related goal.
  2. hivemind_goal_add({ text: "<short description>" }) — capture the returned goal_id.
  3. Confirm to the user with the goal_id and that the goal is team-visible.

Capture a task for later (with resumable context)

When the user parks a tangential task mid-session — "save this for later", "remind me to …", "don't let me forget …", "let's do X later" — store enough context to resume cold later, not just a one-liner. Put the full package in the text of hivemind_goal_add:

hivemind_goal_add({ text:
  "Add rate-limiting to the webhook handler\n\n" +
  "Start here: add a per-IP token bucket on the handler entry path\n" +
  "Files: src/webhook/handler.ts:120-160, src/webhook/limits.ts\n" +
  "Branch: feat/webhook-hardening\n" +
  "Run: pnpm test webhook\n" +
  "Why: bursty clients hammer the endpoint; defer until retry-backoff lands" })

Line 1 is the label. Fill Start here / Files / Branch / Run / Why from the conversation; Start here: (the concrete first action) matters most. (OpenClaw's hivemind_goal_add has no provenance flag, so the row is tagged manual — that's fine; the context is what matters.)

Resume a parked task (automatic context transfer)

When the user says "let's work on that task / goal" or "pick up the <X> task":

  1. hivemind_search({ query: "<topic>" }) or hivemind_index({}) to locate the parked goal, then hivemind_read({ path: "memory/goal/<owner>/opened/<goal_id>.md" }) to pull the full context package back.
  2. Read it as your working context and begin from Start here: using the Files / Branch / Run lines — continue as if the context was never lost.

(Status-move tools aren't exposed on OpenClaw, so leave the goal where it is and just resume the work.)

What NOT to do

  • Do NOT write files anywhere under ~/.deeplake/memory/. OpenClaw's runtime does not route filesystem writes to the Deeplake tables — only the hivemind_* tools above do.
  • Do NOT use hivemind_search to create anything — it's read-only.

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中文简介正在准备中。当前显示原文说明。

activeloopai/hivemind16282026年10月15日 更新

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.

中文简介正在准备中。当前显示原文说明。

activeloopai/hivemind16282026年10月15日 更新

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.

中文简介正在准备中。当前显示原文说明。

activeloopai/hivemind16282026年10月15日 更新

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).

中文简介正在准备中。当前显示原文说明。

activeloopai/hivemind16282026年10月15日 更新

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).

中文简介正在准备中。当前显示原文说明。

activeloopai/hivemind16282026年10月15日 更新

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).

中文简介正在准备中。当前显示原文说明。

activeloopai/hivemind16282026年10月15日 更新

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