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概要と使いどころ
Add another file (resource) to an EXISTING dataset in a PortalJS portal — a data dictionary, methodology, or an additional data file. Turns a single-file dataset into a multi-resource one; the showcase renders a section per resource. Use when a dataset needs a second file, such as a data dictionary, methodology doc, or an additional period's data.
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。
Add a chart (line, bar, area, pie, or scatter) to a dataset's showcase in a PortalJS portal. Installs recharts, writes a reusable Chart component, and renders it in the showcase Views section. Use when visualizing a dataset already registered in datasets.json.
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。
Run or inspect local music analysis and plan or apply beat-, downbeat-, or section-synced video cuts or photo placements. Use for BGM beat edits, rhythm cuts, 卡点剪辑, musical structure, BPM, mood, genre, or instrument questions.
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。
Audit a WordPress plugin's REST surface and produce a standardized audit document proposing Abilities API registrations. Produces a markdown doc with a YAML schema and prose sections that humans and agents can both consume when planning a registration rollout. Works on any WP plugin.
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。
How to pull SEC EDGAR data with the edgartools Python package — company lookup, filings, XBRL financial statements, and filing sections like Item 1A risk factors. Use whenever a task involves SEC filings, 10-K/10-Q data, or company financials.
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。
Standards and audits for writing academic papers, especially ML/NLP submissions to NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL. Covers the author's house prose rules (zero em dashes, zero fluff, every sentence earns its place), verification of hallucinated claims and hallucinated or malformed bibliography entries, the ACL policy on AI writing assistance and what must be disclosed, and best practices for paper structure, experiments, reproducibility checklists, and rebuttals. Use this skill whenever the user is drafting, editing, polishing, restructuring, or reviewing a paper, abstract, intro, related work, rebuttal, or camera-ready; whenever they ask to "clean up" or "tighten" academic writing; whenever citations or a .bib file need checking; and whenever they ask what has to be disclosed about AI assistance. Reach for it even when the user only says "make this section better", "check my references", or "is this ready to submit".
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。
Score a LinkedIn profile out of 100 against a 12-part rubric and rewrite the parts that lose points - headline, about, experience, featured, banner. Use when the user says "optimize my profile", "score my LinkedIn", "rewrite my headline", "fix my about section", or pastes their profile and asks how it reads.
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。
Call MCP server tool for extended capabilities. Check 'MCP Servers' section in system prompt for available servers and tools. When you need to use external service or access specialized functionality.
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。
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Use when the user wants to write blog posts, articles, newsletters, tutorials, case studies, thought leadership pieces, or any long-form content that benefits from research and structured feedback.
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。
Write and revise the Methods section of research papers to ensure reproducibility; use when preparing an IMRAD manuscript or responding to journal/reporting-guideline requirements (e.g., CONSORT/STROBE/PRISMA).
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 a Meta-analysis results section description for funnel plots, including statistical tables (Egger's, Begg's, Trim & Fill) and figure legends. Supports English and Chinese outputs. Use when user provides a funnel plot image and statistics and wants a formatted report.
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 the "Risk of Bias" results section for a meta-analysis based on assessment tables and statistics. Use when the user wants to draft the risk of bias analysis text from provided data tables.
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 the "Results" section for meta-analysis sensitivity analysis based on statistical tables and titles. Use when the user wants to describe sensitivity analysis results or format sensitivity tables for a meta-analysis paper.
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 structured SOAP notes from clinical narratives, transcripts, or existing notes; use when the user needs de-identified clinical documentation organized into Subjective, Objective, Assessment, and Plan sections, with clear assumptions and review points.
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 the Methods section for a meta-analysis paper, including search strategy, screening, quality assessment, data extraction, and statistical analysis.
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。
Creates academic-poster writing packages for LaTeX using beamerposter, tikzposter, or baposter. Use when a user needs poster-ready section copy, figure plans, captions, and package-specific layout decisions for conference or thesis posters.
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。
Assist with biomedical grant proposal drafting, structure, and revision; use when preparing fundable proposal sections, aligning aims and methods, or improving reviewer-facing clarity.
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 LabArchives notebook data, entry metadata, and authorized ELN exports into manuscript-ready academic writing outputs such as Methods sections, data-availability statements, reproducibility appendices, experiment timelines, and submission support notes. Optional bundled scripts can be used to collect or validate source notebook data before writing.
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 structured biomedical outlines for review articles, discussion sections, and thesis proposals. Use when a user provides biomedical keywords, results/discussion text, or a proposal title plus background and needs a directly usable academic writing scaffold.
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。
Adapt scientific abstracts to conference-specific word limits, section rules, and formatting constraints; use when reshaping an existing abstract for submission.
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 phenotype-scoring bioinformatics research designs for any disease context and any user-defined phenotype, pathway, process, signature, or molecular program. Use when a study centers on gene-set or feature-set definition, intersection with DEGs or candidate features, phenotype scoring, feature selection, diagnostic or stratification assessment, immune or cellular-resolution interpretation, network analysis, and optional orthogonal validation. Covers five study patterns (signature discovery, phenotype scoring, feature selection, immune/cellular interpretation, multi-layer validation) and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.
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 QTL colocalization studies that connect eQTL, pQTL, sQTL, or related molecular QTL signals with GWAS loci. Always use this skill whenever a user wants to plan, scope, or structure a locus-level study asking whether a GWAS association and a molecular QTL association may reflect the same underlying causal signal. Covers locus definition, QTL/GWAS source architecture, ancestry and LD alignment, single-locus vs multi-locus strategy, candidate-gene prioritization, optional fine-mapping, linked MR/SMR follow-up, and functional annotation. Always output four workload configurations (Lite / Standard / Advanced / Publication+) with a recommended primary plan, stepwise workflow, method rationale, evidence hierarchy, figure plan, minimal executable version, and strictly verified literature guidance with no fabricated references. Never equate colocalization with causality proof, mediation proof, or automatic target validation. Always include the mandatory Dataset Disclaimer immediately before any workflow section that mentions datasets, repositories, consortia, or public resources.
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 dual-disease shared-transcriptome biomarker and hub-gene research designs from a user-provided disease pair and shared-biology direction. Always use this skill whenever a user wants to design, plan, or build a non-oncology two-disease transcriptome study centered on per-disease differential expression, shared-signal intersection or concordance, PPI-based hub-gene prioritization, diagnostic evaluation across both diseases, immune infiltration context, pathway interpretation, and optional orthogonal validation. Covers five study patterns (shared-DEG-first workflow, hub-gene-first shared-biomarker workflow, hybrid shared-biomarker compression workflow, immune-context shared-biomarker workflow, orthogonal validation workflow) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path...
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 conventional non-oncology bioinformatics research designs from a user-provided disease context, process-related gene family or biological theme, and validation direction. Use when a study centers on multi-dataset bulk transcriptome integration, DEG analysis, process-gene intersection, enrichment analysis, GSEA, PPI hub-gene prioritization, TF/miRNA regulatory networks, ROC-based biomarker evaluation, and immune infiltration analysis. Covers five study patterns (process-DEG discovery, enrichment/GSEA interpretation, hub-gene prioritization, regulatory-network and immune interpretation, multi-layer public validation) and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.
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。