蜂兵虾将
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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Suspicious
medium confidencePurpose & Capability
The name/description (multi-agent hotspot monitoring, analysis, content creation, and memory) matches the included prompts, examples, and Node code: agents for collection, cleaning, pattern recognition, decisioning, and a UnifiedMemorySystem that persists L0-L4 memories. There are no requested environment variables or unrelated binaries, so capability alignment is reasonable.
Instruction Scope
The SKILL.md and AGENT_PROMPTS explicitly direct broad web data collection (Weibo, Zhihu, Douyin, B站, 微信公众号, 36kr, 虎嗅, etc.), creation of persistent user profiles, and continual adaptation/prediction. The runtime instructions assume access to web_search and extract_content_from_websites tools (agent platform services) and instruct persistent recording of user interaction history and templates. This collects and stores behavioral and possibly sensitive content; the instructions mandate some global behaviors (user_confirmation/data_passing 'must be on') which increases privacy surface. The skill's instructions also leave wide discretion to 'proactively prepare' content in background — a broad behavior that may run without fine-grained constraints.
Install Mechanism
Registry metadata lists no install spec (instruction-only), but the package includes many runnable Node artifacts (package.json, dist/, demo.js) and an install.sh, plus an external CDN tarball URL in UPGRADE_REPORT.md. That mismatch is an incoherence: the package appears intended to be installed/run, yet the registry declares no install steps. The presence of an external CDN download link in docs is a higher-risk artifact you should review before running any install script (install.sh) or npm install.
Credentials
The skill requests no environment variables or API tokens in metadata. That is plausible if it relies on the platform's web_search/extraction tools, but the system performs broad data collection and persistent profiling. It will create files/directories under memory/<skillName> and persist L1-L4 data (including user behavior and decision history). Even without declared secrets, this creates privacy and data-retention risks: any sensitive input (user messages, industry data, possible credentials captured during conversation) could be stored. There is also an undocumented CDN URL in docs (external host) — not declared as a runtime dependency but present in repo.
Persistence & Privilege
The skill does not set always:true and does not request elevated platform privileges. However, its code (UnifiedMemorySystem) explicitly creates directories and writes persistent files (L0..L4, shared, logs) under a 'memory' base directory. That is expected for a memory system, but it means the skill will have persistent on-disk state that may contain user data. Confirm where that directory is stored and set appropriate filesystem permissions or sandboxing.
What to consider before installing
This package appears to implement what it claims (web monitoring, content strategy, multi-agent coordination and a persistent memory system), but several things warrant caution:
- Incoherence to review: the registry lists no install steps, yet the archive contains package.json, dist/, demo scripts and install.sh; the docs also include an external CDN tarball URL. Before running anything, inspect install.sh and package.json (and any postinstall scripts) to ensure no unexpected downloads or commands run. Prefer running in a disposable container or VM.
- Privacy & persistence: the UnifiedMemorySystem writes persistent files under memory/<skillName> (L0-L4, shared, logs). The system stores user profiles, interaction histories and outputs. If you will process sensitive data, disable persistent memory or run with restricted filesystem access and clear the memory directory regularly.
- Network behavior: agent prompts instruct scraping many social platforms. The code references use of platform-provided tools (web_search, extract_content_from_websites). Verify whether these rely on your agent platform's network capabilities or whether the package will itself perform HTTP requests. Search the code (install.sh and runtime scripts) for curl/wget/http(s). If the package pulls additional code from the CDN or other remote hosts, treat it as high-risk.
- Least privilege: run demo/installation only after auditing code, and if possible, run it in a sandbox/container with no access to production credentials. Ensure no unexpected environment variables or local config files are read/written outside the memory/<skillName> directory.
- If you need to keep confidentiality: do not enable persistent memory, or restrict access to the memory directory; disable any proactive/background fetching features until you confirm their behavior.
If you want, I can scan the install.sh and package.json (and any scripts referenced there) for network calls, eval/exec usage, or automatic downloads and summarize anything suspicious.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.
