surprise-me by readwiseio/readwise-skills
npx skills add https://github.com/readwiseio/readwise-skills --skill surprise-me你正在分析用户来自 Readwise 和 Reader 的阅读数据,以揭示一个关于他们作为读者和思考者的令人惊讶的洞察。请仔细遵循以下流程。
检查 Readwise MCP 工具是否可用(例如 mcp__readwise__reader_list_documents)。如果可用,请全程使用它们。如果不可用,则使用等效的 readwise CLI 命令(例如 readwise list、readwise read <id>、readwise search <query>)。下面的说明引用了 MCP 工具名称——请根据需要转换为 CLI 等效命令。
广泛撒网。并行运行以下所有操作:
mcp__readwise__readwise_list_highlights,参数 limit=100广告位招租
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触达数万 AI 开发者,精准高效
mcp__readwise__readwise_search_highlightsmcp__readwise__readwise_search_highlights,使用另一个宽泛的术语,如 "surprised" 或 "changed my mind"mcp__readwise__reader_list_tagsmcp__readwise__reader_list_documents,参数 location="archive"、limit=50、response_fields=["title", "author", "category", "tags", "word_count", "reading_progress", "saved_at", "last_opened_at"]mcp__readwise__reader_list_documents,参数 location="shortlist"、limit=50、response_fields=["title", "author", "category", "tags", "word_count", "reading_progress", "saved_at"]然后,至少再对归档列表进行 2-3 次分页以获取更大的样本。
审视所有数据,寻找模式、矛盾和令人惊讶之处。考虑:
呈现一个真正令人惊讶的洞察。不要是像“你读了很多关于技术的内容”这样泛泛的观察——要提供能让他们停下来思考“嗯,我从未注意到这一点”的内容。
格式:
关于你自己,你可能不知道的一件事:
[令人惊讶的洞察——2-3句话,具体且基于他们的实际数据]
然后用证据来支持它:
在呈现洞察之后,提供以下选项:
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77
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GitHub 星标数
86
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9 天前
安全审计
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gemini-cli77
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You are analyzing the user's reading data from Readwise and Reader to surface a surprising insight about them as a reader and thinker. Follow this process carefully.
Check if Readwise MCP tools are available (e.g. mcp__readwise__reader_list_documents). If they are, use them throughout. If not, use the equivalent readwise CLI commands instead (e.g. readwise list, readwise read <id>, readwise search <query>). The instructions below reference MCP tool names — translate to CLI equivalents as needed.
Cast a wide net. Run ALL of these in parallel:
mcp__readwise__readwise_list_highlights with limit=100mcp__readwise__readwise_search_highlights with a broad term like "important" or "interesting"mcp__readwise__readwise_search_highlights with another broad term like "surprised" or "changed my mind"mcp__readwise__reader_list_tagsmcp__readwise__reader_list_documents with location="archive", limit=50, response_fields=["title", "author", "category", "tags", "word_count", "reading_progress", "saved_at", "last_opened_at"]mcp__readwise__reader_list_documents with location="shortlist", limit=50, response_fields=["title", "author", "category", "tags", "word_count", "reading_progress", "saved_at"]Then paginate the archive at least 2-3 more pages to get a larger sample.
Look across ALL the data for patterns, contradictions, and surprises. Consider:
Present ONE genuinely surprising insight. Not a generic observation like "you read a lot about technology" — something that would make them pause and think "huh, I never noticed that."
Format:
Here's something you might not know about yourself:
[The surprising insight — 2-3 sentences, specific and grounded in their actual data]
Then back it up with evidence:
After delivering the insight, offer:
Weekly Installs
77
Repository
GitHub Stars
86
First Seen
9 days ago
Security Audits
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Installed on
gemini-cli77
kimi-cli77
codex77
cursor77
opencode77
github-copilot77
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