agi-is-going-to-arrive/memory-palace-openclaw/memory-palace-openclaw-onboarding
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通过对话引导用户把 Memory Palace 接进 OpenClaw,不依赖 dashboard;for chat-first onboarding, Profile C/D provider collection, probing, fallback explanation, and setup/apply on VPS or terminal-only environments.
Install
npx vskill@latest install agi-is-going-to-arrive/memory-palace-openclaw/memory-palace-openclaw-onboardingSKILL.md
Memory Palace OpenClaw Onboarding
Use this skill when the user wants to install, bootstrap, reconfigure, or troubleshoot Memory Palace onboarding through normal OpenClaw conversation.
This skill is only for onboarding.
- It is not the day-to-day durable memory skill.
- It should not replace
memory-palace-openclaw. - It should assume the user may be on a VPS with no dashboard access.
Default posture
- Prefer tool-driven conversational onboarding first.
- Use the onboarding tools before falling back to raw CLI commands.
- Do not require the dashboard unless the user explicitly asks for it.
- Prefer
stdiotransport unless the user already knows they needsse. - Prefer
Profile C/Dwhen the user can provide real providers. - Fall back to
Profile Bonly when providers are missing, failing, or the user explicitly wants the safest bootstrap path.
Primary onboarding tools:
memory_onboarding_statusmemory_onboarding_probememory_onboarding_apply
Locale rule:
- if the user is speaking Chinese, call these tools with
locale="zh-CN" - if the user is speaking English, call these tools with
locale="en"
Supported provider input forms
When collecting provider values, accept these forms:
Embedding
- Base URL:
https://provider.example/v1https://provider.example/v1/embeddings- API key:
- any normal bearer-style secret string
- Model:
- exact provider model id, for example
Qwen3-Embedding-8B
Reranker
- Base URL:
https://provider.example/v1https://provider.example/v1/rerank- API key:
- any normal bearer-style secret string
- Model:
- exact provider model id, for example
Qwen/Qwen3-Reranker-8B
LLM
- Base URL:
https://provider.example/v1https://provider.example/v1/chat/completionshttps://provider.example/v1/responses- API key:
- any normal bearer-style secret string
- Model:
- exact provider model id, for example
gpt-5.4
Interpretation boundary:
- OpenAI-compatible chat-style configuration is supported.
- If the user pastes a full
/chat/completionsor/responsesURL, treat it as valid input and normalize it to the base automatically. - The current runtime accepts
/responsesas an input alias, but the main write-guard / compact-gist LLM flows still call/chat/completions.
What to ask, in order
Ask only for what is still missing.
- Whether they want the safest bootstrap path or the strongest capability path.
- Whether they need
basicorfull. - Whether they can provide real embedding, reranker, and LLM providers right now.
- The missing provider fields section by section.
Keep the wording simple:
- “If you can provide real providers now, I recommend Profile C or D.”
- “If not, we can start with Profile B first and upgrade later.”
Preferred execution flow
- Start with
memory_onboarding_status. - If the user wants the strongest path and has provider values, run
memory_onboarding_probe. - Read the probe result before applying setup.
- If the embedding probe reports
recommendedDim,detectedMaxDim, ordetectedDim, explicitly tell the user:
- what dimension was detected
- that this is the recommended
RETRIEVAL_EMBEDDING_DIM
- Apply setup only after the probe result is understood:
memory_onboarding_apply
- If onboarding tools are unavailable, fall back to raw CLI:
python3 scripts/openclaw_memory_palace.py onboarding --jsonpython3 scripts/openclaw_memory_palace.py provider-probe --profile c|d ... --jsonpython3 scripts/openclaw_memory_palace.py setup ... --json- On Windows PowerShell, replace
python3withpy -3
- After setup, always verify:
openclaw memory-palace verify --jsonopenclaw memory-palace doctor --jsonopenclaw memory-palace smoke --json
How to interpret probe/setup results
If provider probe passes
- Tell the user C/D is ready to apply.
- If embedding dimension was detected, recommend using that value.
If provider probe reports missing fields
- Tell the user exactly which fields are still missing.
- Ask only for those fields.
- Do not claim that C/D is ready.
If provider probe reports failed providers
- Tell the user which provider failed and why.
- Ask them to fix the address, key, model, or reachability.
- Re-run
provider-probebefore setup.
If setup returns fallbackApplied=true
- State clearly that the requested C/D profile did not stay active.
- State that the environment is now on
Profile B. - Explain that this is a temporary safe fallback, not the target capability path.
- Tell the user to re-probe and then re-run setup after fixing providers.
Profile guidance
Preferred path
Strongly prefer Profile C/D when the user can provide real providers.
Why:
- real embedding
- real reranker
- better retrieval quality
- stronger end-state capability
Safe bootstrap path
Profile B is still the safe bootstrap baseline.
Its hard retrieval boundary is:
- retrieval stays on local hash embeddings
- embedding dimension stays on the local baseline
- reranker stays off
But Profile B can still keep optional LLM-assisted features when valid LLM config is present.
That means:
- write guard can still be enabled
- compact gist can still be enabled
- retrieval quality still does not become true provider-backed C/D retrieval
If no LLM config is provided, those LLM-assisted features stay off and the system continues on the non-LLM path.
Interaction rules
- Do not force the user into the dashboard.
- Do not ask for all fields at once if the probe already narrowed the missing set.
- Do not invent provider values.
- Do not echo secrets back unless the user explicitly asks for the literal command line.
- Prefer the onboarding tools when they are available.
- If tool execution is unavailable, provide the exact commands the user should run.
- If shell execution is available but onboarding tools are also available, still prefer the tools so the conversation stays simple for VPS users.
Anti-patterns
- Do not treat the runtime memory skill as the onboarding skill.
- Do not say C/D is ready before running
provider-probeor equivalent validation. - Do not hide fallback to B.
- Do not describe
Profile Bas equivalent to C/D. - Do not assume the user can open
/setupor any graphical page.
Common Errors
session file locked
If the user runs a local CLI agent turn and hits:
Explain it directly:
- another OpenClaw process is already writing the same session file
- the usual cause is an already-open WebUI or another CLI/gateway process using that same agent/session
Preferred recovery:
- use a fresh session or a temporary agent for the test turn
- or close the process currently holding that session lock
HTTP 401 ... authentication token has been invalidated
If the conversational turn fails with model-auth 401, do not describe it as the onboarding skill failing.
Explain:
- the onboarding skill and onboarding tools were already loaded
- the failure is in the host's current chat-model provider authentication
Preferred recovery:
- refresh or re-login the current model provider token
- or switch the agent to a currently working model, then retry the onboarding conversation
provider probe failure
If a provider probe returns fail, always tell the user:
- which provider failed
- whether the likely cause is base URL, API key, model name, or reachability
- that default apply will only fall back to
Profile Btemporarily - that this does not mean
Profile C/Dis actually ready
Trigger examples
- “帮我把 memory-palace 接进 OpenClaw,不开 dashboard。”
- “我在 VPS 上,只能对话配置,你来引导我装。”
- “帮我配置 Profile C。”
- “provider 报错了,先看哪里没填好。”
- “先帮我探测 embedding 维度,再决定怎么填 env。”
Security
- Security scanPassed, 95 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingextensions/memory-palace/skills/memory-palace-openclaw-onboarding/SKILL.md
Popularity
- Repository stars
- 37
- Repository forks
- 1
- 7-day trend score
- 18
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 28 May 2026, 5 months ago.
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