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".
日本語の概要は準備中です。原文の説明を表示しています。
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.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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 researchまだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
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".
日本語の概要は準備中です。原文の説明を表示しています。
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."
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。