「single」の検索結果

Use when the agent should ask the user for structured input with an in-chat form, including single-select, multi-select, text fields, style pickers, or voice audition choices.

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Turn one pool of existing project media into a batch of distinct, publishable montage cuts instead of a single hero edit. Use for batch montage, one-source-many-outputs, 一源多出, 批量混剪, 批量出片, 矩阵号, 多账号分发, variant batches, deduped cuts, 去重变体, 防搬运, or when the user asks for N different versions of the same footage.

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 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.

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Turn ONE topic into a finished Vox-style paper-collage explainer / ad video, end to end on the Atlas Cloud API + local ffmpeg — script, collage keyframes, motion, voice-over, music, captions, all automated. Use this whenever the user wants a "Vox style" video, a paper/torn-paper collage animation, a "motion collage", a narrated explainer or short ad built from AI-generated collage posters, a scrapbook-style tribute, or wants to turn a topic / product / person into a punchy narrated collage video — even if they don't say the word "Vox". Also use when reproducing Stav Zilber / rom1trs / Higgsfield-style collage ad workflows. Three input modalities: a topic (B-roll), a talking-head video (A-roll mode), or a single photo of a person/product anchored into the collage (C-roll mode). Triggers: "vox video", "collage video", "motion collage", "paper collage explainer", "make a collage ad", "turn this topic into a collage video", "turn my photo/this product shot into a collage video".

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。

Package entire code repositories into single AI-friendly files using Repomix. Capabilities include pack codebases with customizable include/exclude patterns, generate multiple output formats (XML, Markdown, plain text), preserve file structure and context, optimize for AI consumption with token counting, filter by file types and directories, add custom headers and summaries. Use when packaging codebases for AI analysis, creating repository snapshots for LLM context, analyzing third-party libraries, preparing for security audits, generating documentation context, or evaluating unfamiliar codebases.

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Single entry point that routes any ASO, App Store, Google Play, app marketing, paid UA, monetization, retention, reviews, ratings, market-intel, or app-analytics question to the correct specialist skill in this library. Use FIRST whenever the user mentions an app, App Store, Play Store, keywords, ranking, downloads, revenue, subscriptions, screenshots, icon, reviews, competitors, charts, in-app events, launch, press, or ads — but the right specialized skill is not obvious. Triggers: "/aso-router", "/aso-skill", "/aso", "aso help", "help me with my app", "I need ASO", "which skill should I use", or any ambiguous app-marketing request. Skip this router only when the user explicitly invokes a specific skill (e.g. /aso-audit, /keyword-research).

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 existing code-explanation docs into another language, Chinese by default. Translates a whole `CODE_EXPLANATION/` folder into a parallel `CODE_EXPLANATION_<LANG>` copy (e.g. `CODE_EXPLANATION_ZH`), or a single file — either bilingually in place (English + translation interleaved) for small files or as a `<name>_<lang>.<ext>` sidecar copy for larger ones. Keeps filenames, code, identifiers, file paths, and technical terms in English — only the explanatory prose is translated. Use this skill whenever the user wants to translate, localize, or produce a non-English version of code-explanation / codebase documentation: phrases like "translate-explanation", "translate the code explanation", "translate the CODE_EXPLANATION folder", "localize these docs to Chinese", "make a Chinese version of the explanation", or naming any target language for the explanation files. Default to Chinese (ZH) when no language is specified.

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 slide decks and one-pagers that carry an argument rather than decorate one — deck structure, headlines that state the takeaway, charts that make a single point, and the different rules board decks and conference talks follow. Use this to build or fix a pitch deck, board deck, or conference talk, to design a one-pager, or when a deck is dense, unfocused, or being read aloud from the slides. For social graphics, carousels and infographics, use `marketing:visual-content` instead.

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。

Plans and delivers a single project — scope, estimation, scheduling, critical path, tracking, and recovering when it slips. Use this to plan a project, build or challenge a schedule, estimate credibly, track progress meaningfully, or recover a project that is late.

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Buys well — specifying need, running competitive sourcing, negotiating, and category strategy before a contract exists. Use this to run an RFP or vendor selection, negotiate a purchase, consolidate spend across a category, decide between single and multiple suppliers, or bring uncontrolled spending under management.

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Finds the single constraint currently limiting a business's growth and the highest-leverage moves against it, rather than producing a list of everything that could be improved. Use this when growth has stalled or slowed, when deciding where to spend limited time or budget, when revenue rises but profit does not, when prioritizing growth initiatives, or when a business feels busy without compounding.

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Plan and carry a Seedance video from brief through references, storyboard, generation handoff, shot-level review, and targeted repair. Use for an end-to-end Seedance production request; use a narrower prompt skill for a single prompt.

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。

Two stages: first a single-page sheet of numbered panels from an image model, then that sheet fed to Seedance as the reference. The sheet owns order, framing and timing, and the video prompt only has to connect the panels. Use when the user wants a Seedance 2.5 / 2.0 video prompt for this kind of clip (Storyboard grid to video; 中文触发词: 分镜网格转视频, 分镜图, 九宫格, 故事板), or asks how published cases of this type were prompted. Read references/cases.md before drafting.

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。

One small anthropomorphic character carries the whole film. Spell out its looks part by part, write the style as render settings you can measure, and cut the timeline so each block holds a single action goal. Use when the user wants a Seedance 2.5 / 2.0 video prompt for this kind of clip (3D cartoon character short; 中文触发词: 3D 卡通角色短片, 3D 卡通, 皮克斯, 黏土, 卡通角色), or asks how published cases of this type were prompted. Read references/cases.md before drafting.

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Install skill from URL or Git repository to local skills/ directory. When you need to add new skill from GitHub or install SKILL.md from URL. Supports Git repos and single SKILL.md files.

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。

Suite of tools for creating elaborate, multi-component interactive HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX artifacts.

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Unified Python access to 40+ bioinformatics web services; use when you need to query multiple databases (e.g., UniProt/KEGG/ChEMBL/Reactome) with one consistent API in a single workflow, especially for cross-database analysis and identifier mapping.

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Data structure for annotated matrices in single-cell analysis; use when reading/writing .h5ad (or zarr) and exchanging data with the scverse ecosystem.

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Generates complete FAERS-style pharmacovigilance disproportionality research designs from a user-provided drug class, comparator strategy, adverse-event domain, and patient-group stratification. Always use this skill whenever a user wants to design, plan, or build a spontaneous-report safety signal study using FAERS or a similar pharmacovigilance database, especially when the article logic includes product selection, indication-group stratification, MedDRA-based adverse-event extraction, serious-case filtering, suspect-drug and concomitant-exclusion logic, reporting odds ratio analysis, comparator-drug benchmarking, cross-drug comparison, and cautious signal interpretation without causal overclaiming. Covers five study patterns (single-drug disproportionality workflow, multi-drug class comparison workflow, indication-stratified workflow, comparator-controlled signal screening workflow...

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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 FAERS pharmacovigilance study designs for one-drug whole-profile safety mapping using signal detection, subgroup analysis, onset/seriousness characterization, and conservative label-gap interpretation.

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Use when building a weighted gene co-expression network from a bulk expression matrix and a sample group file, filtering variable genes by MAD, identifying co-expression modules with WGCNA, correlating modules with traits, and exporting module-level plots and gene tables. NOT for single-cell RNA-seq, differential expression testing, methylation analysis, or datasets that are too small for WGCNA after quality control.

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Designs complete integrated research plans for bulk transcriptomics, proteomics, metabolomics, and related omics from a user-provided biomedical direction. Always use this skill whenever a user wants to design, scope, or structure a bulk multi-omics or single-omics-plus-clinical study — including disease-focused, mechanism-focused, biomarker-focused, stratification-oriented, or translational projects. It should define the research question, choose the best-fit study pattern, recommend example datasets as reference candidates only, specify the core analysis modules and method choices, propose a validation ladder, and output four workload configurations (Lite / Standard / Advanced / Publication+). Never fabricate datasets, accession numbers, sample counts, metadata completeness, cohort availability, assay coverage, literature references, PMIDs, DOIs, or validation status. Always include the mandatory Dataset Disclaimer immediately before any workflow section that mentions datasets or public resources.

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Generates complete bidirectional multi-phenotype Mendelian randomization research designs from a user-provided exposure family and outcome family. Always use this skill whenever a user wants to design, plan, or build a genome-wide causal-inference study based on publicly available GWAS summary statistics, especially when the article logic includes multiple exposures, multiple outcomes or subtypes, bidirectional MR, IV filtering, IVW as the main estimator, weighted median / MR-Egger / MR-PRESSO sensitivity analyses, leave-one-out testing, heterogeneity / pleiotropy checks, and multiple-testing control with FDR. Covers five study patterns (single-family bidirectional MR, multi-phenotype screening MR, subtype-resolved MR, phenome-style bidirectional causal map, mechanism-prioritized MR follow-up) 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...

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。