Prompts · TypeScript · v0.1.0
Global team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.
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/Catalogue/Prompt/activeloopai/activeloopai-hivemind-hivemind-goals-4
Origin: githubCreate, 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.
by activeloopai · updated 7d ago · imported from GitHub
OpenClaw exposes purpose-built tools for goals. Use them directly — do NOT try to write files via the host filesystem.
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.hivemind_search first to surface any existing related goal.hivemind_goal_add({ text: "<short description>" }) — capture the returned goal_id.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.)
When the user says "let's work on that task / goal" or "pick up the <X> task":
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.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.)
~/.deeplake/memory/. OpenClaw's runtime does not route filesystem writes to the Deeplake tables — only the hivemind_* tools above do.hivemind_search to create anything — it's read-only.No comments yet — start the thread.
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Prompts · TypeScript · v0.1.0
Global team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.
#ai#ai-agents#ai-memory
Prompts · TypeScript · v0.1.0
Global team and org memory powered by Activeloop. ALWAYS check BOTH built-in memory AND Hivemind memory when recalling information.
#ai#ai-agents#ai-memory
Prompts · TypeScript · v0.1.0
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.
#ai#ai-agents#ai-memory
Prompts · TypeScript · v0.1.0
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).
#ai#ai-agents#ai-memory