memory-orchestrator
Orchestrate ClawXMemory retrieval using memory_search first and memory_get for exact record reads
Install / Use
npx skills add dbengoa42-star/edgeclaw --skill memory-orchestratorInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
MarketingSupported Platforms
Our assessment of memory-orchestrator
memory-orchestrator scores 63/100 on our quality scale, 283rd of 295 Marketing skills we index.
Its SKILL.md is 3.0 KB long, split into 7 sections with 1 code example: a solid amount of guidance for an agent.
It has no GitHub stars yet, so there is no community track record; judge it on its content.
Maintenance, license and trust
- The repository was last updated about 6 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 78/100, with 2 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-27. Automated pattern scan on 2026-09-27. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
memory-orchestrator compared with similar skills
All 4 of these similar skills score higher than memory-orchestrator; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| memory-orchestrator (this skill)by dbengoa42-star | 63 | 0 | 6mo ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 85.7k | 12d ago | CLAUDE.md |
| algorithmic-artby anthropics | 100 | 177.9k | 5d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 5d ago | SKILL.md |
| designby nextlevelbuilder | 100 | 130.2k | 6d ago | SKILL.md |
Frequently asked questions
- How do I install memory-orchestrator?
- Run
npx skills add dbengoa42-star/edgeclaw --skill memory-orchestrator. The install tabs above show the steps for each supported agent. - Which AI agents does memory-orchestrator work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is memory-orchestrator safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It declares no license and scores 78/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is memory-orchestrator still maintained?
- The repository was last updated about 6 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
Skill content
View source on GitHubname: memory-orchestrator description: Orchestrate ClawXMemory retrieval using memory_search first and memory_get for exact record reads. Use when the user asks for historical context, project progress, timeline, or profile facts. homepage: https://github.com/OpenBMB/ClawXMemory/tree/main/clawxmemory metadata: {"openclaw":{"skillKey":"openbmb-clawxmemory","requires":{"config":["plugins.entries.openbmb-clawxmemory.enabled"]}}}
Memory Orchestrator
Use this skill when the task depends on conversation history, project status, timeline, or user profile facts.
Primary Path (Tool-first)
- If the user is asking what memory exists or what ClawXMemory currently remembers, use
memory_overviewormemory_listinstead of retrieval. - Otherwise call
memory_searchwith the user's question. - Read
intent,enoughAt, returnedcontext, andrefs. - If the returned context is sufficient, answer from it directly.
- If you need exact verification, call
memory_getwith the smallest relevant id set fromrefs. - If
memory_searchreturns weak or empty evidence, say so clearly and ask a targeted follow-up question.
Fallback Strategy
- Time-oriented question: prefer
refs.l2entries whoselevelisl2_time, then verify withmemory_get({ level: "l2_time", ids }). - Project-oriented question: prefer
refs.l2entries whoselevelisl2_project, then verify withmemory_get({ level: "l2_project", ids }). - Fact/profile question: start with
memory_search, then inspect only the most relevantl1orl0ids if the answer needs precise support.
Tool Usage Notes
- Prefer concise query strings; avoid copying the entire user prompt unless necessary.
- Keep
limitsmall, usually4to8, unless the user asks for exhaustive history. - For browse-only questions, use
memory_overview/memory_listrather thanmemory_search. - Use
memory_getonly aftermemory_searchhas given you the ids worth reading. - If evidence conflicts, prefer the newest verified
l1/l0record and say that the history appears inconsistent.
Minimal Example
User asks: "Where is this project now?"
1) memory_search({ query: "recent project progress", limit: 6 })
2) Read refs.l2 and choose the best l2_project id
3) memory_get({ level: "l2_project", ids: ["<l2-id>"] })
4) If exact wording still matters, read the linked l1 or l0 ids with memory_get
Example User Requests
- "What do you remember?"
Use
memory_overviewormemory_list, notmemory_search. - "What project memory entries exist?"
Use
memory_overviewormemory_list, notmemory_search. - "What is the latest progress on this project?"
Start with
memory_search, then verify the most relevantl2_projectentry withmemory_getif needed.
Guardrails
- Do not fabricate details not supported by retrieved memory.
- Prefer newer verified entries over older ones when there is conflict.
- Do not call
memory_getwith guessed ids. - If retrieval is empty, state uncertainty clearly and ask a targeted follow-up question.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
