This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Literature review for academic and R&D research: search strategy, source assessment, synthesis, and citation management. Use when conducting a systematic literature review, building a bibliography, or preparing a research-grounded report.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
A structured literature-review skill grounded in PRISMA-style protocols (adapted for non-medical fields), source-assessment frameworks, and thematic synthesis patterns.
Before building the review, confirm these inputs. If any is unknown or vague, ASK — do not assume:
Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
search_strategy_builder.py against the question + criteria to
produce a search strategy (database list, queries, filters).python3 litreview/scripts/search_strategy_builder.py \
--input question.json --format markdown
source_quality_scorer.py to grade each on 6 quality dimensions
python3 litreview/scripts/source_quality_scorer.py \
--input sources.json --format markdown
thematic_synthesis_builder.py to cluster sources by theme,
surface evidence strength, identify gaps.python3 litreview/scripts/thematic_synthesis_builder.py \
--input tagged_sources.json --format markdown
A well-framed question makes search and synthesis tractable.
Publish criteria up front; apply consistently.
| Dimension | Question |
|---|---|
| Methodology | Is the method sound? |
| Sample / dataset | Is it adequate for the claim? |
| Peer review | Has it been peer-reviewed? |
| Reproducibility | Is data / code available? |
| Recency | Is it current? |
| Citation impact | Has it been cited / accepted? |
A single sub-dimension is rarely fatal; the combination matters.
| Approach | When |
|---|---|
| Narrative synthesis | Heterogeneous sources; explanatory |
| Thematic synthesis | Multiple sources address common themes |
| Meta-analysis | Quantitative, comparable studies |
| Realist synthesis | Complex interventions; context-mechanism-outcome |
| Scoping review | Mapping a field rather than answering specific question |
For most non-clinical fields, thematic synthesis is the default.
references/search-strategy-and-prisma.md — search patterns, PRISMA disciplinereferences/source-quality-assessment.md — quality dimensions, common assessmentsreferences/synthesis-and-citation-management.md — synthesis approaches, citation hygieneresearch/grants — grant proposals built on literatureresearch/patent — IP-focused literature searchresearch/dossier — intelligence research patternsproduct-team/research-summarizer — synthesizing qualitative research아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design and run statistically rigorous A/B tests and experiments. Use when planning experiments, calculating sample sizes, designing test variants, selecting metrics, analyzing results, or when someone says "let's test that."
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design and analyze A/B tests: sample size, test duration, and statistical significance for conversion experiments. Use when setting up an A/B test, calculating sample size, designing an experiment, or analyzing results.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Sales execution across pipeline, discovery, demos, negotiation, and closing. Use when qualifying opportunities, running MEDDIC discovery, building account plans, handling objections, structuring proposals, or forecasting pipeline.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design ad creative across Google, Meta, LinkedIn, Twitter/X, and TikTok with platform format specs, headline formulas, and A/B testing. Use when writing ad copy, generating headline variations, creating ad sets, or validating creative.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Answer Engine Optimization (AEO): optimize content to be cited by LLMs (ChatGPT, Claude, Perplexity, Gemini) in their answers. Use when designing content for LLM citation, auditing citability, or structuring Q&A schema.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.