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pref0
作者
fliellerjulian
· GitHub ↗
· v1.0.1
1523
总下载
0
收藏
0
当前安装
2
版本数
在 OpenClaw 中安装
/install pref0
功能描述
Learn user preferences from conversations and personalize responses automatically. Preferences compound over time — corrections like "use TypeScript, not JavaScript" are captured and injected into future sessions.
安全使用建议
This skill is internally coherent but you must trust the external service. Before installing: 1) Confirm the vendor (there's no homepage listed) and review their privacy/retention policy — you're sending conversation text and possibly PII. 2) Limit what you send: avoid including secrets, credentials, or sensitive documents in tracked conversations. 3) Prefer using the structured 'preferences' array rather than blindly appending the returned 'prompt' into your system prompt; validate or sanitize that text to reduce prompt-injection risk. 4) Use ?minConfidence to only apply high-confidence preferences. 5) Have a process to rotate/revoke PREF0_API_KEY and to test DELETE /v1/profiles/<userId> to satisfy data-deletion requests. 6) Monitor usage/cost and logs for unexpected activity. If you cannot verify the vendor or their data-handling practices, treat this as higher-risk and consider not installing.
功能分析
Type: OpenClaw Skill
Name: pref0
Version: 1.0.1
The skill is suspicious due to two primary reasons: 1) It explicitly instructs the AI agent to send the full conversation history, including potentially sensitive user data, to an external third-party API at `https://api.pref0.com/v1/track` (SKILL.md). 2) It also instructs the agent to fetch a `prompt` field from the same external API (`https://api.pref0.com/v1/profiles/:userId`) and directly inject it into its own system prompt (SKILL.md). While the stated purpose is benign (personalization), this mechanism creates a significant supply chain prompt injection vulnerability, as a compromised `api.pref0.com` could inject arbitrary, malicious instructions into the agent's operating context.
能力评估
Purpose & Capability
Name/description (preference learning) align with the declared requirement (PREF0_API_KEY) and the API endpoints in SKILL.md. Sending conversations to https://api.pref0.com and fetching a stored profile is coherent with the stated purpose.
Instruction Scope
Runtime instructions explicitly tell the agent to POST full message histories and to append the service-provided 'prompt' directly into the system prompt. That behavior is expected for a preference service but raises privacy and prompt-injection concerns (the skill will transmit user messages and accept external prompt text that the agent is asked to use verbatim).
Install Mechanism
No install spec or code files — the skill is instruction-only. Nothing is downloaded or written to disk by the skill bundle itself.
Credentials
Only a single credential (PREF0_API_KEY) is required, which is proportionate for a hosted API. There are no unrelated env vars or config paths requested. Note: the API key grants the external service access to posted conversations, so it should be treated as sensitive.
Persistence & Privilege
The skill is not always:true, does not request system-wide changes, and is user-invocable. It does permit autonomous invocation by default (disable-model-invocation is false) which is normal for skills but increases the importance of vetting the external service.
如何使用
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install pref0 - 安装完成后,直接呼叫该 Skill 的名称或使用
/pref0触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.1
pref0 1.0.1
- Improved API documentation to clarify track and profile endpoints, including more detailed response fields for conversation tracking.
- Added a ready-to-use prompt field to the profile API response for easier system prompt integration.
- Now, the profile endpoint (`GET /v1/profiles/:userId`) returns the `prompt` directly alongside learned preferences and patterns.
- Created notes.txt file (contents not specified in this changelog).
v1.0.0
Initial release of pref0 — automatic user preference learning and personalized response skill.
- Learns user preferences (corrections, explicit choices, behavioral patterns) from conversation history
- Automatically injects learned preferences into future sessions for personalized responses
- Provides easy API endpoints to track conversations, fetch preferences, generate system prompts, and delete profiles
- Confidence-based extraction with compounding for repeated signals
- Simple setup: just provide your PREF0_API_KEY environment variable
元数据
常见问题
pref0 是什么?
Learn user preferences from conversations and personalize responses automatically. Preferences compound over time — corrections like "use TypeScript, not JavaScript" are captured and injected into future sessions. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 1523 次。
如何安装 pref0?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install pref0」即可一键安装,无需额外配置。
pref0 是免费的吗?
是的,pref0 完全免费(开源免费),可自由下载、安装和使用。
pref0 支持哪些平台?
pref0 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 pref0?
由 fliellerjulian(@fliellerjulian)开发并维护,当前版本 v1.0.1。
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