Skill flagged — suspicious patterns detected
ClawHub Security flagged this skill as suspicious. Review the scan results before using.
记一下
v0.2.0像发消息一样记录一切(灵感/想法/知识/收支/日记/任务/引用),AI 自动分类、标签、关联,让知识自然生长。 支持微信/飞书消息输入,零摩擦记录。统一存储,多视图呈现(闪记视图/日记视图/周报视图)。 触发:用户发送任何想记录的内容时自动调用。
⭐ 0· 69·0 current·0 all-time
by@yankj
MIT-0
Download zip
LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Suspicious
medium confidencePurpose & Capability
The skill claims both a CLI ('just-note') and automatic WeChat/Feishu message ingestion via OpenClaw Gateway. However the package manifest refers to a bin/just-note executable (package.json and docs), but that executable is not present in the provided file list. Many docs/test reports assert features (AI message integration, high test accuracy, weekly/monthly summaries) while other files explicitly state LLM and message integration are 'not implemented' or 'TODO'. This mismatch between claimed capabilities and included artifacts is a coherence concern.
Instruction Scope
SKILL.md gives concrete Bash pseudocode to classify content, call an LLM, and write markdown files under memory/just-note/*.md. The runtime instructions don't instruct reading unrelated system config or secrets, and saved files are scoped under memory/just-note. However the instructions reference OpenClaw gateway hooks and an LLM calling mechanism without providing the actual integration code; the provided LLM-calling pseudocode (call_llm / sessions_send / curl) is ambiguous. The skill also uses unspecified variables (e.g., $SOURCE) which are not declared, so runtime behavior may be inconsistent.
Install Mechanism
There is no install spec (instruction-only), so nothing arbitrary is downloaded during install. The only included script is publish.sh which is for publishing and calls the clawhub CLI. No external download URLs or extract operations are present in the provided files.
Credentials
The skill declares no required environment variables or credentials, which matches the fact it intends to store notes locally. However some runtime snippets refer to $SOURCE and to potential LLM API endpoints or tokens (in TODO notes) but do not declare or require them. If the author later wires in direct LLM API calls or message connectors, additional credentials would be required; currently that is not present or declared.
Persistence & Privilege
The skill does not request always:true and is user-invocable. It will write files to a local 'memory/just-note' directory per its instructions, which is expected for a note-taking tool. There is no evidence it attempts to modify other skills or global agent settings.
What to consider before installing
Plain-language checklist before installing or running this skill:
- Missing CLI: The package.json and docs expect a bin/just-note executable, but that file is not included here. Do not assume the CLI exists — ask the author for the actual executable or inspect the 'bin/just-note' script before running.
- LLM & messaging not implemented: The SKILL.md contains pseudocode for calling an LLM and routing WeChat/Feishu messages, but multiple files state LLM/message integration is TODO. Confirm how the skill will call LLMs (OpenClaw sessions_send, a local CLI, or a direct API) and which credentials (if any) it will require before enabling message auto-ingest.
- Docs conflict: Some test reports claim 100% AI accuracy and completed features while other files explicitly list them as unimplemented. Treat the reported test results with caution; ask for a reproducible test or demo.
- Filesystem access: The skill uses Bash/Read/Write/Grep. That allows it to read and write files — intended for storing notes under memory/just-note, but verify the implementation to ensure it does not read or exfiltrate unrelated files.
- publish.sh behavior: The included publish script calls the clawhub CLI and requires the user to be logged in; publish.sh is for distribution and is not required for runtime, but read it before running.
Recommended steps:
1) Ask the author for the missing bin/just-note executable or the real implementation of the CLI. 2) Request clarification / code showing how LLM calls and message routing will be performed and which credentials (if any) will be needed. 3) Run the skill in an isolated test environment (sandbox or container) and inspect what files it creates/writes. 4) If you plan to enable automatic message ingestion, verify the integration path and scope of permissions for any connectors (WeChat/Feishu) before granting them.
Confidence is medium because the skill appears honest in intent but the inconsistent/missing artifacts and contradictory test claims prevent a stronger 'benign' verdict.Like a lobster shell, security has layers — review code before you run it.
aivk978c7k0avg3t1a4xwe4dssmp183mkmmknowledgevk978c7k0avg3t1a4xwe4dssmp183mkmmlatestvk978c7k0avg3t1a4xwe4dssmp183mkmmnotevk978c7k0avg3t1a4xwe4dssmp183mkmmproductivityvk978c7k0avg3t1a4xwe4dssmp183mkmm
License
MIT-0
Free to use, modify, and redistribute. No attribution required.
