| name | discover-wikipedia-rabbit-holes |
| description | Curate a small, surprising Wikipedia reading list that mixes a user's established interests with adjacent and unfamiliar subjects. Use for daily or recurring Wikipedia recommendations, intellectual rabbit holes, anti-filter-bubble reading, or a themed learning trail with discussion prompts. |
Discover Wikipedia Rabbit Holes
Build a compact reading path that rewards curiosity instead of reproducing a popularity list.
Workflow
- Infer the user's interests from the current conversation and any preferences they provide. If context is thin, choose a broad mix rather than blocking on questions.
- Search the live web for candidate Wikipedia articles. Verify that every recommended page exists and use its canonical URL.
- Select 5–8 articles with this balance:
- roughly half closely connected to known interests;
- several adjacent subjects that create useful bridges;
- at least one genuinely unexpected wildcard.
- Prefer specific phenomena, obscure events, unusual systems, intellectual history, and concepts with strong explanatory value. Avoid generic hub pages, listicles, breaking news, and several near-duplicates.
- Briefly explain why each article is worth reading and how it connects to the preceding article or the user's interests.
- End with one synthesis question that invites discussion or a note in a digital garden.
Output
Use the user's language. For each item provide the linked article title and a one- or two-sentence hook. Keep the whole digest scannable and do not summarize the complete article in advance.
When asked for a recurring digest, vary subjects across runs using any prior recommendations visible in context. State clearly that the skill can produce the digest but does not itself create a scheduler; use the environment's task or automation mechanism only when the user asks to schedule it.
