research-issues

Research current challenges in Japanese NLP 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 challenges. Use the following defaults for the rest of the steps:

• Topic label for output headings: "Japanese NLP Current Challenges" (use "日本語NLP 現状の課題" only when the user's query was written in Japanese)
• Keywords for Step 1 (local dataset survey): japanese nlp, llm, evaluat, benchmark, embed, speech, morpholog — These broad keywords give a cross-category snapshot for inferring coverage gaps
• WebSearch queries for Step 5: cover challenge-language across multiple sub-fields:
  • japanese NLP challenges ${YEAR_NOW} overview
  • 日本語 NLP 課題 ${YEAR_NOW}
  • japanese LLM limitations evaluation ${YEAR_NOW}
  • 日本語 自然言語処理 問題点 未解決 ${YEAR_NOW}
  • japanese NLP benchmark error analysis ${YEAR_NOW}
• Report title: ## 🔍 Japanese NLP Issue Report (as of ${REPORT_DATE_EN}) instead of ## 🔍 Issue Report for "$ARGUMENTS" (use ## 🔍 日本語NLP 現状の課題レポート (${REPORT_DATE_JP}時点) only when output language is Japanese)
• Section 1 (Overview): write a broad 3–4 sentence overview covering the most pressing challenges across active sub-fields (LLM evaluation, low-resource domains, embedding quality, speech, benchmarks)