Research

Generate academic research proposals for PhD applications. Use when user asks to "write a research proposal", "create PhD proposal", "generate research plan", "撰写研究计划", "写博士申请", "doctoral proposal", or mentions specific research topics for PhD application. Supports STEM, humanities, and social sciences with field-specific adaptations. Follows Nature Reviews-style academic writing conventions. Supports both English and Chinese output based on user preference.

Look up current research information using the Parallel Chat API (primary) or Perplexity sonar-pro-search (academic paper searches). Automatically routes queries to the best backend. Use for finding papers, gathering research data, and verifying scientific information.

Search the web, extract URL content, and run deep research using the Parallel Chat API and Extract API. Use for ALL web searches, research queries, and general information gathering. Provides synthesized summaries with citations.

Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).

Comprehensive citation management for academic research. Search Google Scholar and PubMed for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries. This skill should be used when you need to find papers, verify citation information, convert DOIs to BibTeX, or ensure reference accuracy in scientific writing.

Efficient database search tool for bioRxiv preprint server. Use this skill when searching for life sciences preprints by keywords, authors, date ranges, or categories, retrieving paper metadata, downloading PDFs, or conducting literature reviews.

Use this Skill for every economics-paper introduction, intro, opening section, first-two-pages, 英文引言, or 经济学论文引言 task, especially requests to read a completed paper body/正文 and write directly usable English introduction prose. It drafts, rewrites, shortens, restructures, outlines, audits, positions, or fact-checks introductions for empirical, structural, theory, historical, measurement, and mixed economics papers. It also checks whether an introduction's contribution, novelty, gap, or citatio...

Always invoke this skill when the user wants a conclusion, concluding section, final paper section, paper ending, or 结论 for an economics manuscript—including requests to read an empirical, theoretical, or structural economics paper and write a ready-to-use English conclusion. Use it to draft, rewrite, shorten, audit, or fact-check the ending even when the user does not name the skill. It reads the paper body and uses only supported findings, mechanisms, boundaries, and implications. Do not us...

Always invoke this skill when the user wants an abstract or 摘要 for an economics research paper from a manuscript, completed paper body, model, data, or results—including requests to read an empirical, theoretical, or structural economics paper and write a ready-to-use English abstract. Use it to draft, rewrite, compress, audit, or fact-check an economics abstract even when the user does not name the skill. It reads the paper body and verifies every substantive claim. Do not use for generic su...

Always invoke this skill for ANY request to write, propose, choose, rank, rewrite, compare, or audit an economics paper title—including 中文 requests for 论文标题, 英文标题, 标题候选, 推荐标题, or 备选标题. Invoke it when the user asks for one recommended English title plus alternatives from an empirical, theoretical, or structural economics manuscript, even if the skill is not named. It reads the paper body and treats every displayed title as a factual promise. Do not use for section, table, figure, news, or book...

Decomposes underspecified requests by classifying gaps (missing info, ambiguity, false premises) and generating targeted clarifying questions. Produces a confirmed problem statement before any implementation begins. For sharpening a request that already exists; not for open-ended requirement discovery from a vague idea (use the research command).

Independent, execution-grounded review of a build phase against its done-when requirements. Runs the suite first, verifies each requirement with evidence and a trace, returns PASS or FAIL with specific findings.

Deep web research with Brave Search API. Find sources, extract content, and compile comprehensive reports. Use when a user asks to research a topic on the web, find information online, compile a research report, search the internet for sources, do a deep dive on a subject, gather web sources for a report, or investigate a topic thoroughly using multiple online sources.

Build voice AI applications using Microsoft's VibeVoice — open-source frontier voice synthesis, recognition, and real-time conversation. Use when: building voice assistants, adding TTS/STT to applications, creating real-time voice chat, voice cloning.

When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," or "SEO health check." For building pages at scale to target keywords, see programmatic-seo. For adding structured data, see schema-markup.

When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," or "new user experience." For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.

When the user wants to find, qualify, and build a list of prospects to reach out to \u2014 across B2B SaaS, general B2B, or local small businesses. Also use when the user mentions \"prospecting,\" \"build a prospect list,\" \"find prospects,\" \"find leads,\" \"lead gen list,\" \"find SaaS companies that,\" \"find B2B companies,\" \"find local businesses,\" \"ICP-fit accounts,\" \"who should we go after,\" \"outbound list,\" \"target account list,\" \"find clients near me,\" \"businesses with...

When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions \"onboarding flow,\" \"activation rate,\" \"user activation,\" \"first-run experience,\" \"empty states,\" \"onboarding checklist,\" \"aha moment,\" \"new user experience,\" \"users aren't activating,\" \"nobody completes setup,\" \"low activation rate,\" \"users sign up but don't use the product,\" \"time to value,\" or \"first session experience.\"...

When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions \"A/B test,\" \"split test,\" \"experiment,\" \"test this change,\" \"variant copy,\" \"multivariate test,\" \"hypothesis,\" \"should I test this,\" \"which version is better,\" \"test two versions,\" \"statistical significance,\" \"how long should I run this test,\" \"growth experiments,\" \"experiment velocity,\" \"experiment backlog,\" \"IC...

When the user wants to research, profile, or analyze competitors from their URLs. Also use when the user mentions 'competitor profile,' 'competitor research,' 'competitor analysis,' 'profile this competitor,' 'analyze competitor,' 'competitive intelligence,' 'competitor deep dive,' 'who are my competitors,' 'competitor landscape,' 'competitor dossier,' 'competitive audit,' or 'research these competitors.' Input is a list of competitor URLs. Output is structured competitor profile markdown fil...

Search Yelp businesses and reviews, compare local options, and audit listing quality with official APIs, public pages, and safe action boundaries.

Conduct AI-led research with autonomous literature review, hypothesis generation, analysis, and synthesis while human provides vision.

Support veterinary understanding from pet care to clinical practice and research.

Evidence-based therapeutic techniques — CBT, ACT, mindfulness, and reframing for anxiety, rumination, and behavioral patterns.