research-trends

Research Japanese NLP trends for topic: "$ARGUMENTS" by combining the bundled dataset with the latest web information.

Instructions

Preamble — Establish the current date

Before doing anything else, run this once and remember the values — every subsequent step that mentions a year, month, or report date refers to them:

echo "YEAR_NOW=$(date +%Y)"
echo "YEAR_PREV=$(($(date +%Y) - 1))"
echo "REPORT_DATE_EN=$(LC_TIME=C date '+%B %Y')"
echo "REPORT_DATE_JP=$(date '+%Y年%-m月')"

Substitute these values everywhere this skill writes ${YEAR_NOW}, ${YEAR_PREV}, ${REPORT_DATE_EN}, or ${REPORT_DATE_JP} below. Do not hardcode dates — the skill must always reflect the current month.

Step 0 — Handle empty input

If $ARGUMENTS is empty or blank, treat it as a request for a general overview of current Japanese NLP trends. Use the following defaults for the rest of the steps:

• Topic label for output headings: "Japanese NLP Overall Trends" (use "日本語NLP 全体トレンド" only when the user's query was written in Japanese)
• Keywords for Step 1 (local dataset survey): japanese nlp, llm, bert, embed, speech, morpholog, translat — These broad keywords give a cross-category snapshot of the most popular resources
• WebSearch queries for Step 5: cover multiple active sub-fields rather than one topic:
  • japanese NLP trends ${YEAR_NOW} overview
  • 日本語 NLP 最新動向 ${YEAR_NOW}
  • japanese LLM embedding benchmark ${YEAR_NOW} github
  • 日本語 自然言語処理 注目 モデル ${YEAR_NOW}
  • huggingface japanese models trending ${YEAR_NOW}
• Report title: ## 📊 Japanese NLP Trend Report (as of ${REPORT_DATE_EN}) instead of ## 📊 Trend Report for "$ARGUMENTS" (use ## 📊 日本語NLP 全体トレンドレポート (${REPORT_DATE_JP}時点) only when output language is Japanese)
• Section 1 (Overview): write a broad 3–4 sentence overview covering the major active sub-fields (LLMs, embeddings/RAG, speech, morphological analysis, benchmarks)

Then continue normally from Step 1 using the above defaults.