ai-news-fetcher_skill

This skill fetches the latest AI news and generates bilingual English-Japanese markdown articles organized by date for easy consumption.

Python

3

GitHub Stars

4

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill masayan1126/masayan-uni-code-plugins --skill ai-news-fetcher

PROMPTS.md3.9 KB
REFERENCE.md4.4 KB
SKILL.md450 B
WORKFLOW.md2.3 KB

Overview

This skill fetches the latest AI news from the web using the Tavily MCP pipeline and generates bilingual (Japanese-English) markdown articles organized by date. It automates retrieval, summary, and formatting so you get ready-to-publish bilingual posts. The output is structured, dated markdown suitable for blogs, newsletters, or internal reports.

How this skill works

The skill queries Tavily MCP to discover and scrape recent AI articles, then extracts key facts, headlines, and publication metadata. It generates concise summaries and produces side-by-side or sectioned Japanese and English markdown content, adding dates and basic metadata for each item. The process supports configurable fetch windows and summary lengths to match editorial needs.

When to use it

You need daily or weekly AI news digests in bilingual markdown format.
Preparing bilingual newsletters, blog posts, or internal briefings on AI developments.
Automating aggregation of headlines and summaries for content teams.
Translating short news summaries into Japanese and English for distribution.
Rapidly generating dated archives of AI news for research or compliance.

Best practices

Set clear fetch time windows (e.g., last 24 hours or last 7 days) to limit noise.
Adjust summary length to fit target channel: shorter for social, longer for blog posts.
Review and edit sensitive or high-stakes items before publishing; automated summaries may omit nuance.
Include source links and publication dates in each markdown item for traceability.
Monitor and rotate source lists periodically to avoid bias and stale feeds.

Example use cases

Daily AI newsletter: produce dated bilingual markdown with 5–10 top stories and summaries.
Blog content pipeline: auto-generate draft bilingual posts ready for human editing and enrichment.
Research archive: create a chronological markdown repository of AI news for trend analysis.
Internal briefing: weekly bilingual digest for engineering and leadership teams.
Multilingual social media planning: generate concise bilingual blurbs from news summaries.

FAQ

The skill is designed for Japanese-English outputs by default; extending to other languages requires adding translation steps or configuring the pipeline to use alternate language models.

How are sources chosen and credited?

Sources are discovered via the configured Tavily MCP pipelines and each article item includes its original link and publication date so you can verify and credit the source.

Is the generated markdown production-ready?

Generated markdown is formatted and organized, but a short human review is recommended for tone, legal checks, and accuracy before publication.