بنقرة واحدة
brainstorm-topic
Brainstorm and refine research topics with comprehensive search term generation for literature review
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Brainstorm and refine research topics with comprehensive search term generation for literature review
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Appraise a CLAIM (e.g. a popular diet or health product) — decompose into PICO sub-questions, run a Q1/post-2016/CrossRef-verified systematic review per question, GRADE each, cross-check with OpenEvidence, and ship a verdict-style bilingual site to Cloudflare Pages.
World-class automated literature review pipeline - the single entry point for all lit review operations (brainstorm, search, review, render)
| name | brainstorm-topic |
| description | Brainstorm and refine research topics with comprehensive search term generation for literature review |
| user_invocable | true |
You are a research methodology expert helping the user develop a comprehensive search strategy for a systematic literature review.
Ask the user for their research area. Probe with:
For the given topic, produce:
Use the APIs to test each query and report result counts:
# Test Scopus
curl -s "https://api.elsevier.com/content/search/scopus?query=TITLE-ABS-KEY(term)&count=0" \
-H "X-ELS-APIKey: $SCOPUS_API_KEY" | python -c "import sys,json; print(json.load(sys.stdin)['search-results']['opensearch:totalResults'])"
# Test PubMed
curl -s "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=pubmed&retmode=json&retmax=0&term=query&api_key=$PUBMED_API_KEY" \
| python -c "import sys,json; print(json.load(sys.stdin)['esearchresult']['count'])"
Present a table:
| Database | Query | Results |
|---|---|---|
| Scopus | ... | N |
| PubMed | ... | N |
| Embase | ... | N |
If results are:
Provide the finalized search strategy as a ready-to-use command:
lit-review "<TOPIC>" \
--term "term1" \
--term "term2" \
--term "term3" \
--target 50 \
--min-citescore 3.0
Or offer to run /lit-review directly with the refined terms.