2,001 件 ・ 関連度順
概要と使いどころ
Use when creating journal cover images, generating scientific artwork prompts, or designing graphical abstracts. Creates detailed prompts for AI image generators to produce publication-quality scientific visuals.
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。
Converts an audited medical research gap into a complete, structured, gap-traceable study design. Always use this skill whenever a user already has one or more candidate research gaps and wants to transform them into an executable biomedical research plan rather than re-run broad topic ideation. Covers six gap-to-design patterns (evidence-completion, mechanism-resolution, cell-state/context-mapping, translation-bridge, causality-upgrade, population/stage-specific) and always outputs one recommended primary protocol, a gap-to-design dependency map, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, and verified design-support literature rules. Never fabricate references. Preserve claim-evidence discipline and do not replace a topic-specific gap with a generic workflow.
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。
Generates complete Mendelian randomization study designs from a user-provided exposure and outcome direction. Always use this skill whenever a user wants to design, plan, or build a Mendelian randomization study — even if phrased as "help me write a paper on X", "design an MR study for Y", or "I want to test whether A causally affects B using GWAS". Covers core two-sample MR design, optional bidirectional follow-up, optional multivariable MR, IV selection logic, ancestry alignment, harmonization, IVW as the default primary estimator, weighted median / MR-Egger / MR-PRESSO / leave-one-out sensitivity analyses, Steiger directionality, heterogeneity / pleiotropy checks, and explicit claim-boundary control. Always outputs four workload configs (Lite / Standard / Advanced / Publication+) with a recommended primary plan, stepwise workflow, method rationale, validation ladder, figure plan, minimal executable version, and strictly verified literature guidance with no fabricated references.
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。
Assesses whether a medical research topic is worth starting now by separating true novelty from pseudo-novelty, auditing real feasibility under stated resource constraints, and forcing a concrete start / narrow / redesign / stop decision. Always require explicit assumptions and never fabricate references, datasets, resource availability, precedent studies, or publication claims.
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。
Designs cell-based and animal-based validation plans that translate computational, omics, biomarker, genetic, or clinical findings into experimentally testable validation routes. Always use this skill whenever a user wants to move from an in silico, statistical, or clinical association finding toward wet-lab validation using cell systems, organoid-like systems, xenograft or genetically relevant animal models. It should define the exact claim to test, separate mechanism-testing from association-support and translational-support goals, choose the best-fit model family, specify perturbation strategy, readouts, controls, sequencing of experiments, and four workload configurations (Lite / Standard / Advanced / Publication+) with one recommended primary plan. Never fabricate model availability, reagent availability, species relevance, assay feasibility, phenotype penetrance, expected effect sizes, validation success, or literature references.
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。
Writes complete, publication-grade figure legends that can stand on their own. Use when writing or revising figure legends for any scientific figure — bar charts, line graphs, scatter plots, box plots, heatmaps, survival curves, flow cytometry plots, western blots, microscopy images, or schematic diagrams. Also triggers on "write a figure legend for", "help me describe this figure", "my figure needs a legend", "write Figure 1 legend", or "what should a figure legend include".
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。
Turns your protocol and analysis workflow into publication-ready Methods text. Use when writing or revising the Methods section of a biomedical manuscript, ensuring it complies with reporting guidelines (CONSORT, STROBE, PRISMA, TRIPOD), matches what is in the Results section, and satisfies journal-specific word limits and declarations. Also triggers on "write my methods", "revise my methods section", "how to report my statistics", "what do I need to include in methods for [study type]", or "make my methods CONSORT-compliant".
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。
Research what Chinese internet users actually said in the last 30 days across Weibo, Xiaohongshu (RED), Bilibili, Zhihu, Douyin, WeChat public accounts, Baidu and Toutiao: engagement-weighted ranking, cross-platform clustering, cited Markdown/JSON/HTML reports. Also shows today's cross-platform hot-search board (全网热榜, --hot) and can add Hacker News / GitHub / Reddit or an installed upstream last30days for X/YouTube/TikTok.
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。
Use when evaluating Bill Ackman-style concentrated long theses, activist campaigns, high-conviction multiyear bets, and public narrative plus fundamental catalysts.
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。
Search and retrieve content from Reddit. Get posts, comments, subreddit info, and user profiles via the public JSON API. Use when user mentions Reddit, a subreddit, or r/ links.
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。
Search and install agent skills from ClawHub, the public skill registry. Use when needing new capabilities, searching for skills, installing skills, or updating installed skills.
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。
Discover public GitHub repositories that import defineTask from @a5c-ai/babysitter-sdk and maintain a deduplicated catalog of those repositories in docs/repo-with-babysitter-processes.md. Excludes any repo named "babysitter" (to filter out forks of this monorepo). Invoke when asked to find, discover, catalog, or refresh "repos using babysitter", "babysitter in the wild", or "who else is using babysitter".
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。
This skill should be used when the user asks to "find skills in the wild", "assimilate popular workflows", "discover SKILL.md files in repos", "research external skills", "find workflow patterns", "survey the skill landscape", "what skills exist out there", or wants to investigate public repositories for extractable processes, babysitter plugins, and reusable procedural insights. Searches GitHub for SKILL.md files, classifies repos by archetype, and maintains structured research under docs/reference-repos/.
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。
Translate a Beamer `.tex` lecture to a Quarto RevealJS `.qmd` mirror. Multi-phase: TikZ extraction → slide-by-slide translation → citation conversion → automatic QA parity check. Use when user says "translate to quarto", "port to revealjs", "make an html version", "convert this beamer to quarto", "mirror this lecture in qmd", or after a Beamer deck is ready for web publication. Output lands in `Quarto/`.
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。
Render Quarto `.qmd` slides to HTML and sync to `docs/` for GitHub Pages. Use when user says "deploy", "publish the slides", "ship to pages", "push the lecture live", "render and publish", or after Quarto edits that need to go public. NOT for local Quarto render only — use `quarto render` directly for 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。
End-to-end R data analysis pipeline — exploration → cleaning → regression → publication-ready tables and figures. Use when user says "analyze this dataset", "run a regression on X", "explore this CSV", "full analysis workflow", "get me summary stats and a regression", or points at a `.csv`/`.rds`/`.dta` and asks for empirical results. Produces numbered R scripts in `scripts/R/` and outputs to `output/`.
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。
End-to-end Stata replication pipeline — scaffolds numbered `.do` files in `scripts/stata/`, executes them via the `stata-mcp` MCP server, captures logs and outputs to `output/`, and produces publication-ready tables (esttab) and figures (graph export). Mirrors `/data-analysis` for R-first projects. Use when user says "stata replication", "set up Stata pipeline", "scaffold the .do files", "run Stata analysis", "AEA replication package in Stata", or when a project's analysis language is Stata not R.
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。
Keeps a project's to-do list and memory in GitHub issues — files each finding (from a review, an audit, or the user) as its own issue without duplicates, lists the open issues that bear on the current work, and closes an issue with a comment recording what was wrong, what was tried, what worked, and how it was fixed. Use when review findings or a list of problems should become tracked work (a paper's misleading claims, a codebase's bugs, improvements for later), when starting or resuming work and deciding what to do next, or when a fix has landed and its issue should be closed with a record. Needs the GitHub CLI; warns before posting to a public repository.
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。
AI DevKit · Systematic structural or multi-file refactors across any stack while preserving behavior and public contracts. Use for reorganizing modules, boundaries, naming, APIs/contracts, staged refactor plans, or refactor risk review.
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。
Generate cloned narration for the content workspace. Use local IndexTTS2 with the canonical lossless Pluviobyte reference for every local video, voice audition, digital-human narration, and subtitle-ready audio render. Preserve MiniMax only for public-facing articles or tutorials that teach users to connect through the relay service; never use MiniMax for local video production.
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。
Analyze a public or local reference video, isolate a time range, deconstruct its layout, motion, timing, and transitions, then build an original verified motion replica with reusable templates and final MP4 QC. Use when the user says 复刻这个视频效果, 参考这个视频做同款动效, 拆解前 N 秒, 还原方框/连线/卡片动画, or provides a video or URL as a motion reference rather than asking to copy its footage or script.
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。
Chinese AI/tech writing de-AI editor for posts, X/Twitter threads, technical essays, product notes, model reviews, and public-writing drafts. Use when the user asks to 去AI味, 改得像本人, 写推特post, 精修中文AI技术文章, or complains about AI-flavored shells such as 不是A而是B, 真正/其实/本质上, 更重要的是, 冒号讲义腔, 空泛总结, 顺滑但没作者判断的稿子.
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。
Publish an Agentlas package to Agent Cloud or the public Hub.
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。
Staff a task only from public Agentlas Hub agents.
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。