Agent Skills
› mohitagw15856/pm-claude-skills
› wiki-summary
wiki-summary
GitHub通过调用维基百科无密钥REST API获取话题的实时摘要，解决模型训练数据过时问题。支持模糊标题消歧、多语言及事实核查，严格区分原文与模型补充内容，并明确标注信息更新差异。
触发场景
查询特定话题的最新维基百科摘要
验证事实以对比当前信息与训练记忆
询问某主题是否发生变化或需最新资料
安装
npx skills add mohitagw15856/pm-claude-skills --skill wiki-summary -g -y
SKILL.md
Frontmatter
{
"name": "wiki-summary",
"homepage": "https:\/\/mohitagw15856.github.io\/pm-claude-skills\/skill\/wiki-summary.html",
"metadata": {
"openclaw": {
"emoji": "🧠"
}
},
"description": "Fetch Wikipedia's current summary of any topic with zero API keys — the REST summary endpoint via curl, for answers that need today's article rather than training-data memory. Use when asked what does Wikipedia say about X, get me the current summary of a topic, check a fact against Wikipedia, or has this article changed. Produces the live extract with the article link, disambiguation handling, and a clean separation between what Wikipedia says and what the model adds."
}
Wiki Summary Skill
The model already knows what Wikipedia said at training time; this skill fetches what it says now — which matters for anything living: people's roles, company facts, ongoing events, populations, "current CEO" questions. Wikipedia's REST API serves a clean summary per article over keyless HTTPS. The skill's discipline is attribution: the fetched extract is Wikipedia's voice, dated today; anything the model adds around it gets labeled as such.
What This Skill Produces
- The live extract — Wikipedia's current summary paragraph(s) for the topic, quoted as the source
- The link and metadata — canonical URL, and the description line ("American computer scientist")
- Disambiguation handling — when the title is ambiguous, the options, not a guess
- The command — exact curl, rerunnable
Required Inputs
Ask for these if not provided:
- The topic — resolved to an article title (spaces → underscores); ambiguous names get the disambiguation treatment, not a silent pick
- Language edition — en default; the endpoint pattern works on any edition (
de.wikipedia.org,ja.wikipedia.org) and the user's question may belong in one - Why they're asking — a fact-check wants the specific claim compared; a primer wants the extract; "has this changed" wants fetched-vs-recalled differences called out
Framework: The Endpoint and the Attribution Rules
- The call:
curl -s "https://en.wikipedia.org/api/rest_v1/page/summary/Alan_Turing"→ JSON:title,description,extract(the summary text),content_urls.desktop.page(canonical link),type. URL-encode the title; spaces become underscores. - Search first when the title is uncertain:
curl -s "https://en.wikipedia.org/w/rest.php/v1/search/title?q=turing&limit=5"→ candidate titles. Atype: "disambiguation"response means list the options and ask — a confident summary of the wrong John Smith is worse than a question. - Attribution is the product: the extract is quoted or clearly framed as "Wikipedia currently says…" with the link. Model elaboration goes outside that frame, labeled. A fact-check answer states: the claim, what the live article says, and whether they match.
- Freshness honesty both directions: fetched beats recalled for living facts — but Wikipedia itself lags and errs; for high-stakes facts the answer notes it's one (good) source, and breaking-news topics may be mid-edit.
- The changed-since-training move: when the fetched extract contradicts what the model would have said, say so explicitly — "training-era memory said X; the live article now says Y" — that delta is often exactly what the user was probing for.
Output Format
[Article title] — [description line]
[The live extract, as Wikipedia's voice]
[Fact-check mode: the claim vs. the extract, verdict stated] [Model additions, if any, under a labeled line]
Source: [canonical article URL] · fetched [date] · rerun: [exact curl]
[Disambiguation case: the candidate list and the ask]
Quality Checks
- The extract is attributed to Wikipedia and dated — never blended into model voice
- Ambiguous titles produced options, not a guess
- Fact-checks compare the specific claim to the specific sentence
- Training-memory vs. live-article deltas are called out when found
- The canonical URL appears
Anti-Patterns
- Do not paraphrase the live extract into model voice — the fetch's value is the attribution
- Do not silently pick among namesakes — disambiguate out loud
- Do not treat Wikipedia as final authority for high-stakes facts — one good source, framed as such
- Do not answer "what does Wikipedia say" from memory — that question is a fetch instruction by definition
- Do not skip the URL — the link is the receipt
版本历史
- 54fad50 当前 2026-07-19 12:38
