1,677 件 ・ 関連度順
概要と使いどころ
Use when selecting or composing behavior-preserving refactoring techniques after structural evidence is known, especially when multiple candidate transformations, preconditions, or ordering choices must be compared.
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。
Complete B2B SaaS marketing agency powered by 90 AI agents across 17 specialties. This is the entry point for ALL marketing requests. Routes to the right specialist team: content marketing, SEO, paid media, social media, email marketing, design, sales enablement (including technical presales — demos, proofs of concept, security questionnaires), product marketing, account-based marketing (ABM), partnerships and channel programs (co-marketing, marketplace GTM, channel conflict and deal registration, partner economics), growth, analytics, project management, or client operations. Use this skill when the request spans multiple disciplines or when unsure which specialist to invoke. Also triggers on: marketing help, marketing team, marketing agency, what can you do, marketing capabilities.
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 a task needs the judgment of an Elementary School Teacher — interpreting a running record or fluency check against grade-level benchmarks, deciding whether a struggling reader needs a Tier 2 intervention, running a self-contained classroom's daily schedule across multiple subjects, implementing (not writing) an IEP/504 accommodation with fidelity, or writing a parent-conference summary grounded in assessment 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。
Use when a task needs the judgment of a dental assistant — sequencing instrument transfer during a procedure, troubleshooting a retake-worthy radiograph before re-exposing the patient, tracing a failed sterilization-cycle indicator back to the affected instrument batches, or timing a chairside material mix against its working-time window across multiple prepped teeth.
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 a task needs the judgment of a Computer Numerically Controlled (CNC) Tool Programmer — calculating stepover from a scallop-height/surface-finish spec instead of picking one by feel, deciding whether a toolpath needs a dry run before cutting material on an unfamiliar post-processor/machine pairing, verifying datum consistency across multiple part setups, or diagnosing why cycle time jumped after a "minor" parameter change.
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 a task needs the judgment of a Commercial and Industrial Electronics Repairer — diagnosing a VFD fault trip on a production line, tracing a PLC I/O fault back to the sensor, the wiring, or the ladder logic, selecting arc-flash PPE for live-panel diagnostic work, triaging multiple simultaneous down-lines by downtime-cost-per-hour, or deciding drive/board swap versus component-level repair.
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 a task needs the judgment of a billing and posting clerk — generating an invoice against a rate/contract schedule, applying an incoming payment across multiple open invoices, processing a credit memo or adjustment, or investigating an aging-report discrepancy.
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 a task needs the judgment of a Bioinformatics Scientist — designing a differential-expression or GWAS analysis with correct multiple-testing correction, calling and triaging variants from NGS data using genotype-likelihood confidence rather than raw allele counts, interpreting a BLAST/DIAMOND homology search, choosing or building a genomics pipeline (aligner, caller, normalization method) for a specific data-generating process, or judging whether a computational-biology analysis's statistical design actually supports the biological claim being made. Distinct from a bioinformatics-technician (executes and QC-gates an established pipeline someone else designed) and a data-scientist (general product/experimentation judgment, not genomics-specific statistics) — this role owns which method and statistical model a genomics question requires, and why.
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 a task needs the judgment of an Acute Care Nurse — tracking early warning score trends across a higher patient ratio than ICU to catch silent deterioration before crisis, distinguishing expected post-operative recovery variation from a true complication requiring escalation, triaging competing needs across multiple simultaneous patients, balancing analgesia against oversedation risk by real-time response rather than fixed dosing, and verifying genuine discharge readiness rather than checking a form.
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。
Build comprehensive chromatin accessibility maps by aggregating ATAC-seq and DNase-seq narrowPeak data across multiple ENCODE experiments, donors, and labs. Use when the user wants to answer "where is chromatin accessible in my tissue?" by combining peak calls into a union peak set. Handles cross-lab variation, ATAC vs DNase platform differences, and ENCODE blocklist filtering.
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。
Conduct rigorous cross-study meta-analysis of scRNA-seq data from ENCODE, integrating multiple single-cell transcriptomic datasets for a tissue/cell type. Use when the user wants to answer "what cell types exist in my tissue and what genes define them?" by combining scRNA-seq data across donors, labs, and platforms. Follows the Mawla et al. 2019 framework for assessing cross-study reproducibility, TIN-based quality filtering, and detection-limit-aware interpretation. Handles batch correction (Harmony/Seurat), dropout awareness, cross-contamination artifacts, and platform-specific biases. Use this skill for ANY scRNA-seq integration task, cross-dataset comparison, cell atlas construction, or reproducibility assessment involving ENCODE single-cell 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。
Build comprehensive DNA methylation maps by aggregating WGBS (Whole Genome Bisulfite Sequencing) data across multiple ENCODE experiments, donors, and labs. Use when the user wants to answer "where is DNA methylated/unmethylated in my tissue?" by combining per-CpG methylation data into tissue-level methylation profiles. Handles coverage filtering, identifies hypomethylated regions (HMRs) and partially methylated domains (PMDs), and manages cross-lab variation.
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。
Guide for multi-experiment batch operations: QC screening, batch download, comparison, and report generation across many ENCODE experiments simultaneously. Use when users need to process 5+ experiments together, create experiment comparison tables, perform batch quality checks, or generate summary reports. Trigger on: batch analysis, multiple experiments, bulk processing, experiment comparison, batch QC, multi-sample, batch download, experiment table, summary report, collection 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。
Build comprehensive chromatin contact maps by aggregating Hi-C loop calls (BEDPE) across multiple ENCODE experiments, donors, and labs. Use when the user wants to answer "what regions are in 3D contact in my tissue?" by creating a union catalog of chromatin loops. Handles resolution-aware anchor matching, cross-lab variation, and Hi-C-specific quality metrics.
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。
Integrate multiple ENCODE data types (RNA-seq, ATAC-seq, Histone ChIP-seq, TF ChIP-seq) for a tissue/cell type to build a comprehensive regulatory landscape. Use when the user wants to answer "what are the enhancers, promoters, and regulatory elements active in my tissue, and which transcription factors control them?" by layering expression, chromatin accessibility, histone marks, and TF binding data. Follows the Mawla et al. 2023 framework for cross-assay integration of islet cell type-specific data. Handles chromatin state annotation (ChromHMM), enhancer-gene linkage, TF motif enrichment, and cell type-specific regulatory element identification. Use for ANY multi-omic analysis, enhancer discovery, regulatory network construction, or epigenomic characterization using ENCODE 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。
Plan and execute integrative analysis combining multiple ENCODE experiments for cross-dataset or multi-omic workflows. Use when the user wants to combine experiments, perform cross-dataset comparison, multi-omic integration, peak overlap analysis, differential binding, signal correlation, chromatin state segmentation, enhancer-gene linkage, or any analysis that requires merging or comparing data from two or more ENCODE experiments. Covers same-assay cross-sample, multi-omic same-sample, cross-organism, and perturbation integration designs. Guides compatibility checks, batch effect detection, normalization, integration strategy selection, and provenance documentation.
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。
Rapid UI prototyping — generates 3 visually distinct HTML/CSS components from a text prompt and serves them in a live browser gallery. Use when user runs /prototype, asks to "prototype a UI", "mock up a component", "generate HTML mockups", "create UI variations", "design exploration", "quick UI concept", or wants to see multiple visual approaches to a component. Also trigger when user says "show me different ways to build...", "explore different designs for...", or wants rapid visual exploration of a UI idea — even without saying "prototype" explicitly.
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。
Analyzes git commit history and generates professional changelogs with semantic versioning, conventional commit support, and multiple output formats (Keep a Changelog, Conventional, GitHub). Use when editing CHANGELOG.md, CHANGELOG.txt, or HISTORY.md files, preparing release notes, creating releases, bumping versions, updating changelog, documenting changes, writing release notes, tracking changes, version bump, tag release, or when user mentions "changelog", "release notes", "version history", "release", "semantic versioning", or "conventional commits".
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。
Archive multiple completed OpenSpec changes at once. Use when archiving several parallel changes. Also use for a plural archive request - "openspec bulk-archive", "opsx bulk-archive", "openspec archive all", or "openspec archive these changes".
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 this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.
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 a single feature idea, improvement, or bug into ONE well-structured GitHub issue. TRIGGER when: the user wants to file/open/create an issue, turn a feature idea or improvement into a ticket, or capture something missing or broken as a ticket. DO NOT TRIGGER when: breaking work into multiple issues or planning a body of work → a planning skill; writing a full Product Requirements Document → creating-prd; the idea is still fuzzy and unhardened → grilling-ideas first.
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。
Manage fleets of local AI agents: lifecycle, monitoring, task assignment, and resource control. Use when running multiple CLI agents via an orchestrator like AI Maestro.
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。
Manage fleets of local AI agents — spawn, supervise, route tasks, monitor progress, and shut down workers cleanly. Use when coordinating multiple agents on parallel workstreams.
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 an institutional-grade commercial real estate underwriting model — input schema (T-12 income, T-3 trailing, rent roll, debt terms, exit assumptions), calc engine (Cap Rate, NOI, Cash-on-Cash, IRR, DSCR, Debt Yield, ROI, Equity Multiple, levered & unlevered returns).
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。