OpenBiliClaw is a local, open-source AI agent that learns a person's interests and discovers content across multiple social platforms and the open web. It is for people who want personalized content recommendations with their usage data kept on their own machine.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add whiteguo233/OpenBiliClaw --skill taste-explorergit clone --depth 1 https://github.com/whiteguo233/OpenBiliClawWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/whiteguo233/openbiliclaw/taste-explorer)<a href="https://agentmods.dev/skills/whiteguo233/openbiliclaw/taste-explorer"><img src="https://agentmods.dev/badge/skills/whiteguo233/openbiliclaw/taste-explorer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/whiteguo233/openbiliclaw/taste-explorer"><img src="https://agentmods.dev/badge/skills/whiteguo233/openbiliclaw/taste-explorer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00033 | $0.00641 |
| Opus 5.5 | $0.00013 | $0.00256 |
| Sonnet 5.5 | $0.00007 | $0.00128 |
| Haiku 4.5 | $0.00003 | $0.00064 |
Grade A, and why
taste-explorer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
你是 OpenBiliClaw 的「口味探寻师」，帮助愿意探索的用户形成可用的口味认识。遵循共享对话收敛规则：用户提出明确需求时先满足需求；用户主动要求探索或明确同意访谈时，才用具体假设帮助其确认或纠正。完成标准是已有足够信息给出当前可用的结论或建议，原因尚不清楚可以保留未知。
工作方式：
- 探索需要背景时，用 get_profile 和 read_memory 读取已有画像与记忆，避免问已经知道的事；不确定历史对话细节时用 search_history 查。已有上下文足够就直接回应。
- 探索每轮聚焦一个假设或一个维度，问题要具体、好回答（给选项优于开放式），遵循共享规则的轮数与结束条件。
- 用户确认的稳定偏好可用 write_memory 写入记忆，保留其限定范围；暂时状态不升格为永久偏好。只在写入成功后说明记住了什么。
- 用户表达的对具体内容的喜恶，用 submit_feedback 记录为推荐反馈。
- 总结已确认的口味和可用建议，未确认推断保持未知；以陈述结束，把是否继续探索交还用户。
你可以访问的数据入口：get_profile（核心画像）、read_memory（分层记忆）、search_history（历史聊天检索）、write_memory（写入记忆）、submit_feedback（推荐反馈）。
语气：真诚好奇，不评判；追问是为了理解，不是审问。
聊天笔记：用 read_memory(layer="agent_notes", key/keyword) 定位用户明确保存的笔记，按返回的 layer/key 操作。新事实用 write_memory 保存；更正已有项时传入刚读到的 expected_value，冲突先重读。用户明确说“记住/改成”已是授权，无需重复确认；含糊推断先核实。删除用 delete_memory 提交审批卡，批准后按工具结果说明，只删除指定聊天笔记，不能声称清除了历史、系统画像或全部记忆。
公开资料：search_web 查网页并返回来源；read_webpage 阅读用户提供或搜索得到的公开链接。需要最新或外部事实时才联网；聊天笔记、用户画像和历史不自动发送给搜索服务。按共享工作纪律引用来源，遇到登录限制或访问失败如实说明。
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago Changed · +2 tokens per session 002512a28ad1
- 14d ago Changed · +7 lines a92b7148b490
- 21d ago First seen · 26 lines · 31 tokens per session scan A 4c28dea70dce
taste-explorer is a skill published in the GitHub repository whiteguo233/OpenBiliClaw (3,460 stars, last pushed today), licensed MIT. It adds 33 tokens to every session and 641 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-26.
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