Huo15 Knowledge Base
v0.7.2火一五知识库技能 - 基于 Andrej Karpathy 的 LLM Knowledge Bases 方案。每个企微 Agent 独立隔离,自动在 Agent 工作目录下创建专属知识库。触发词:知识库、入库知识库、查询知识库、编译知识库、体检知识库、同步知识库、激活知识库。
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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
medium confidencePurpose & Capability
The name/description (LLM-driven knowledge base per-agent) matches the scripts and SKILL.md: activation, ingest, compile, search, lint and optional memory bridge. The code operates on per-agent kb/ directories under ~/.openclaw/agents/{agent-id}/agent/kb which is coherent with the stated 'agent-isolation' design.
Instruction Scope
Runtime instructions and scripts explicitly bundle raw document contents into LLM prompts (compile_prompt.md, lint_prompt.md) and instruct use of OpenClaw/OpenClaw-run to call the LLM. That means raw documents and wiki entries are packaged and sent to an external LLM provider for compilation/analysis — expected for this skill but a data‑exfiltration/privacy consideration. Scripts also write and modify files under agent data directories (creating config.json, index files) which is consistent with activation but important to note.
Install Mechanism
No remote install/downloads or external archives; the skill is delivered as script files and is instruction-only (no automated external installer). There is no brew/npm/URL-based install. The highest‑risk install pattern (downloading/executing code from arbitrary URLs) is not present.
Credentials
The skill declares no required env vars but the scripts read AGENT_DIR and various files under ~/.openclaw/agents/* (including models.json). kb-llm.py loads provider configuration (baseUrl, apiKey) from the agent models.json to call the configured LLM. This is proportional to the stated purpose (it must use the configured provider) — but it means the skill will use existing provider credentials and will transmit document contents to that provider. Verify that the configured provider/baseUrl is trusted and that models.json does not contain unexpected keys or endpoints.
Persistence & Privilege
The skill is not always:true and does not require platform-level permanent inclusion. Some scripts (install-all-agents.sh) will iterate over all agents under ~/.openclaw/agents and create kb/ directories and configs for each — a bulk/admin action that writes into every agent workspace. That behavior aligns with the provided 'batch activate' script but should be run deliberately (it modifies multiple agent directories).
Assessment
This skill appears to do what it claims: create per-agent knowledge bases and use an LLM to compile and lint entries. Important cautions before installing/using:
- Data exposure: compile and lint build prompt files that include the full contents of your raw documents/wiki entries and instruct the environment to send them to the configured LLM provider. Do NOT ingest sensitive or confidential documents unless you trust the configured provider and understand its data handling.
- Credentials use: kb-llm.py reads models.json under your agent directories to discover provider baseUrl and apiKey and will use those credentials to call the provider. Confirm models.json points to a trusted provider and does not contain unexpected endpoints.
- Bulk activation: scripts/install-all-agents.sh will create kb/ and config.json across all agents under ~/.openclaw/agents — review that script before running as it will write into every agent workspace.
- Test in isolation: activate the skill for a single test agent first (or run scripts in a sandbox), verify the provider and outputs, and confirm no sensitive data is being sent.
- Portability note: some scripts use sed -i '' (BSD syntax) which may behave differently on Linux; this is not a security issue but could affect operation.
If you want, I can: (1) point out the exact lines where documents are concatenated into prompts, (2) show how to edit the scripts to avoid sending raw content (e.g., only send metadata or excerpts), or (3) produce a safe checklist to run before using the skill in production.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.
