research-issues
Investigate current challenges, limitations, and proposed solutions in Japanese NLP for a topic. Surveys the existing awesome-japanese-nlp-resources dataset to see what already exists, then web-researches known problems and ongoing efforts to produce a digestible issue report.
npx skills add taishi-i/awesome-japanese-nlp-resources --skill research-issues --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
Research current challenges in Japanese NLP for topic: "$ARGUMENTS" by combining the bundled dataset with the latest web information. ## Instructions ### Preamble — Establish the current date Before doing anything else, run this once and remember the values — every subsequent step that mentions a year, month, or report date refers to them: ```bash echo "YEAR_NOW=$(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 `$ARGUMENTS` is empty or blank, treat it as a request for a **general overview of current Japanese NLP challenges**. Use the following defaults for the rest of the steps: - **Topic label** for output headings: "Japanese NLP Current Challenges" (use "日本語NLP 現状の課題" only when the user's query was written in Japanese) - **Keywords for Step 1** (local dataset survey): `japanese nlp`, `llm`, `evaluat`, `benchmark`, `embed`, `speech`, `morpholog`
- Instructions
- Preamble — Establish the current date
- Step 0 — Handle empty input
- Step 1 — Interpret the topic
- Step 2 — Locate the data file
- Step 3 — Survey existing resources (inline scoring)
- Step 4 — Identify challenge angles to investigate
- Step 5 — Web research
- Step 6 — Cross-reference and synthesize
- Step 7 — Format the issue report
- Step 8 — Edge cases
echo "YEAR_NOW=$(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')" echo "RESOURCES_PATH=$RESOURCES_PATH"
What does the research-issues skill do?
Investigate current challenges, limitations, and proposed solutions in Japanese NLP for a topic. Surveys the existing awesome-japanese-nlp-resources dataset to see what already exists, then web-researches known problems and ongoing efforts to produce a digestible issue report.
How do I install it?
Run `npx skills add taishi-i/awesome-japanese-nlp-resources --skill research-issues --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From taishi-i/awesome-japanese-nlp-resources, a repository with 1,000 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.