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query-wikipedia

Skill0 starsChanged 8 months agoApache-2.0View on GitHub

Query summary from Wikipedia for a given topic.

2 other projects use a version of this.

Adopted by

Most recently taken up by

  • Other versions2 projects use a version of this.

    Word for word · 2

    1. google-ai-edge/gallery★ 25k100% same
    2. jegly/Box★ 995100% same

    Edited · 0

    None found.

    Wrote their own version · 0

    None found.

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository10 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Call the run_js tool using index.html and a JSON string for data with the following fields:

    line 10
  2. Distinctive:

    If the exact answer to the user's question is not found in the extract, briefly state this, then proactively offer a related piece of …

    line 17

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Query Wiki

Instructions

Call the run_js tool using index.html and a JSON string for data with the following fields:

  • topic: Required. Extract ONLY the primary entity, person, or event (e.g., "2026 Oscars", "Albert Einstein"). You MUST REMOVE all specific question details, action words, or conversational text (e.g., do NOT include words like "winner", "best picture", "who won", "history of"). Search for the broad subject so the tool can return the main article.
  • lang: Required. The 2-letter language code. This code MUST match the language of the keywords you provided in the topic field. Use standard codes, e.g., "en" (English), "es" (Spanish), "zh" (Chinese), "fr" (French), "de" (German), "ja" (Japanese), "ko" (Korean), "it" (Italian), "pt" (Portuguese), "ru" (Russian), "ar" (Arabic), "hi" (Hindi).

Constraints:

  • Provide a concise summary (1-3 complete sentences) to conserve context. Always ensure your response ends with a finished sentence. your response MUST BE written in the SAME language as the user's original prompt.
  • For recurring events or time-sensitive facts, query the specific iteration (e.g., "2026 Oscars"). If the user omits the year, default to the current year.
  • If the exact answer to the user's question is not found in the extract, briefly state this, then proactively offer a related piece of information that was found in the text.

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