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BB totalreclaw

End-to-end encrypted, decentralized memory for OpenClaw. A native kind:memory provider — recall i... 核心能力: - 智能代理领域的专业化AI辅助工具 - 基于高人气开源Skill深度优化升级 - 移除风险代码,增强安全性和稳定性 适用场景: - AI代理增强、记忆管理、自主决策 - 独立开发者与一人公司效率提升 - 自动化工作流与智能决策辅助 差异化:经过深度优化,去除原始风险代码,清理外部依赖引用,增强元数据和触发关键词,完全适配SkillHub平台规范。 触发关键词: memory, plugin, native, encrypted, totalreclaw, openclaw, decentralized

ClawHub Agent Skills author: 天轰穿 v1.0.0 MIT-0 2 files body ≈ 2 023 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process B 73/100 · Nearly there — weak spots: result and completion, inputs and preconditions, progress reporting

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
83/100
safety, quality, tests
Safety 60%
93
Quality 40%
68
Run on models
none yet
Process rating
B
73/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Risky intent medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The purpose itself is risky: wallets, browser password stores, offensive security. Even an honest implementation gives the agent access to things that cost money.

For the author

Explain in the description why the access is needed and how it is limited; add tests that show refusals on dangerous requests.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 3

✓ No critical or high findings

Medium and low: 3
  • medium Risky intent intent-wallet-secrets SKILL.md:54
    Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target
    The 12-word recovery phrase MUST NEVER enter chat or the agent's LLM context. The plugin's browser-based pair flow handles phrase generation and import. Never echo it, never ask the user to paste it,
  • low Dangerous commands cmd-background-process SKILL.md:91
    Starts a background / autostarted process (quoted — discussed, not commanded)
    **Do NOT use `tr pair --json` for this.** The CLI holds the pair WebSocket in a subprocess that Skill平台's ~30s shell-tool timeout kills — the WS then drops, and when the user submits their phrase the
    quoted
  • low Risky intent intent-wallet-secrets SKILL.md:92
    Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target (quoted — discussed, not commanded)
    2. Surface the **url** and **pin** to the user verbatim (read from the JSON; never invent values): "Open `<url>` in your browser, enter PIN `<pin>`, and generate or paste your 12-word recovery phrase.
    quoted

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "tools"

Process rating: all ten parameters 73/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 12 steps
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 4 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2023 tokens
  • 100Running it twice. Mutating operations check current state
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • +2Single-language instructions
  • +3Description length 371: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 12 items
  • +4Has examples (4 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.

External checks

ClawHub: suspicious
This memory skill is coherent in purpose, but it needs Review because it combines persistent automatic memory capture with destructive cleanup and autonomous restart instructions that reduce user control.
LLM: suspicious (high) · 17 Jul 2026