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cccskills

「design」の検索結果

1.2万 件 ・ 関連度順

概要と使いどころ

Plan, design, author, preview, publish, and manage Power BI reports across requirements, page design, local PBIR/PBIP edits, validation, screenshots, Fabric upload/download, and rebinding. Use for report lifecycle work; use semantic-model-authoring for model or DAX changes and fabriciq for data questions. Triggers: plan Power BI report, design report page, edit PBIR, preview PBIP, publish report, rebind 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。

microsoft/skills-for-fabric1,2532026年10月5日 更新

Design review and validation workflow for KiCAD projects via MCP tools. Triggers on: "review my design", "check for errors", "audit", "DRC", "ERC", "find problems", "design review", "is this ready", "validate", "check my schematic", "check my PCB", "what's wrong", "run checks", "pre-fab 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。

mixelpixx/Konnect1,2372026年10月12日 更新

Use when asked to run Design Error Detection (quick defect scan), find design errors in a Simulink model, perform root cause analysis on DED findings, fix division-by-zero, overflow, dead logic or out-of-bounds defects detected by SLDV, or diagnose why missing coverage cannot be achieved (dead logic blocking coverage objectives). Do NOT use for requirement verification, test generation, Inf/NaN detection, active logic analysis, or coverage measurement.

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。

matlab/simulink-agentic-toolkit1,2352026年10月15日 更新

Design stable, compatible public APIs using extend-only design principles. Manage API compatibility, wire compatibility, and versioning for NuGet packages and distributed systems.

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。

Aaronontheweb/dotnet-skills1,2302026年10月12日 更新

Designs pegRNAs and nicking guides for prime editing (PE) -- choosing the nick/strand, tuning the primer-binding site (PBS) and reverse-transcription template (RTT) as a per-locus panel, selecting the PE system (PE2/PE3/PE3b/PE4/PE5/PEmax/PE7), adding MMR-evading and PAM-disrupting silent edits, appending epegRNA 3' motifs (tevopreQ1/mpknot), and ranking with PRIDICT/DeepPrime. Covers twinPE/PASTE for large insertions and the prime-vs-base-editing decision. Use when designing a scarless point mutation, small insertion/deletion, or any of the 12 base conversions without a double-strand break, when efficiency is low and MMR inhibition or pegRNA stabilization is needed, or when routing a large insertion to an integrase method. Generic guide scoring and base editing are separate 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。

GPTomics/bioSkills1,2232026年8月15日 更新

Identifies differential m6A methylation between conditions from MeRIP-seq paired IP/input data using exomePeak2 (GC-bias-aware differential via its bam_ip/bam_input control + bam_treated_ip/bam_treated_input treatment arms), QNB beta-binomial, MeTDiff HMM, and RADAR, plus the paired-symmetric edgeR/DESeq2-on-peak-counts route when batch/lot covariates need fixed-effect handling that exomePeak2's API does not accept. Covers paired vs unpaired vs interaction designs, batch confounding and per-lot meta-analysis, the stoichiometry-vs-expression-vs-IP-efficiency confound, and effect-size filtering against under-powered N=2 designs. Use when comparing m6A across two or more conditions, choosing between exomePeak2/QNB/RADAR/MeTDiff for a design, handling batch confounding when exomePeak2's API is too rigid, distinguishing real hyper/hypo-methylation from expression shifts, applying effect-size thresholds, or planning orthogonal stoichiometry validation (GLORI/SAC-seq/m6Anet mod_ratio).

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。

GPTomics/bioSkills1,2232026年8月15日 更新

Designs pooled sgRNA libraries for CRISPR knockout, interference (CRISPRi), activation (CRISPRa), Cas12a multiplex, base-editor, and prime-editor screens. Covers on-target scoring (Rule Set 2, Azimuth, DeepSpCas9, CRISPRon), off-target scoring (CFD, MIT), TSS-relative positioning for CRISPRi/a (Horlbeck, Dolcetto, Calabrese), PAM-variant chemistries, control-guide composition, oligo cloning architecture, and library QC. Use when choosing a genome-wide library (GeCKOv2 vs Avana vs Brunello vs TKOv3 vs Inzolia), designing a focused or paralog-focused custom library, picking CRISPRi vs CRISPRa TSS windows, deciding control-guide proportions, or diagnosing library skew and dropout in a freshly cloned pool.

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。

GPTomics/bioSkills1,2232026年8月15日 更新

Designs and analyzes in vivo CRISPR screens in animal tumor models, organoids, and immune-cell adoptive transfers. Covers bottleneck math (250x cells/sgRNA requires ~25M cells implanted; impossible for most syngeneic models, forcing focused libraries), focused library design (Manguso 2017 Nature 547:413 immune screen; Chen 2015 tumor screens), CRISPR-StAR intrinsic-control screening (Uijttewaal 2025 Nat Biotechnol 43:1848), clonal-dynamics-limited detection, tumor-explant DNA recovery, syngeneic vs xenograft vs PDX considerations, and the relationship to downstream MAGeCK / drugZ analysis. Use when designing in vivo CRISPR screens for tumor / immune / metastasis biology, choosing focused vs genome-wide for animal models, addressing bottleneck-induced clonal collapse, picking the syngeneic / xenograft / PDX model, integrating in vivo with in vitro results, or applying CRISPR-StAR for animal experiments.

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。

GPTomics/bioSkills1,2232026年8月15日 更新

Designs and analyzes pooled prime-editor (PE) screens for installing precise genetic variants without bystander confounding. Covers pegRNA design with PRIDICT and PRIDICT2 for predicting per-pegRNA editing efficiency, pegRNA architecture (spacer + scaffold + PBS + RTT), PE2/PE3/PE3b/PEmax variants, MOSAIC in situ saturation mutagenesis, the PRIME pooled-screen methodology (Ren 2023; ~3,699 ClinVar variant screens), chromatin context as a major locus-level determinant of PE efficiency, scaffold-incorporation and indel byproduct quantification with CRISPResso2, and the cross-modal validation strategy of PE + base-editor screens for variant function. Use when designing a pegRNA library for variant installation, choosing between BE and PE for a specific edit, predicting pegRNA efficiency before library synthesis, analyzing PE screen output, distinguishing intended-edit from scaffold-incorporation, or scaling PE screens to thousands of variants.

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。

GPTomics/bioSkills1,2232026年8月15日 更新

Cross-method decision tree for calling hits in pooled CRISPR screens. Catalogs statistical models (MAGeCK RRA, MAGeCK MLE, BAGEL2, drugZ, JACKS, Chronos, CERES), experimental designs each is built for, failure modes outside design domain, reconciliation when methods disagree, multiple-testing and effect-size thresholds, the order of operations (count -> QC -> CN-correct -> hit-call -> validate), the second-best-sgRNA conservative rule, and consensus-hit strategy. Use when choosing among MAGeCK / BAGEL2 / drugZ / JACKS / Chronos for a given design, reconciling disagreement across two or three methods on the same screen, deciding whether to require consensus, gating downstream validation by hit-confidence tier, or interpreting unstable hit lists across reruns.

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。

GPTomics/bioSkills1,2232026年8月15日 更新

Designs covalent inhibitors and warheads targeting cysteine, lysine, serine, threonine, tyrosine, and aspartate residues, with explicit handling of warhead reactivity (acrylamide, chloroacetamide, vinyl sulfone, sulfonyl fluoride, fluorosulfate, aldehyde, boronate, nitrile), reversibility (kinact/Ki, t_residence), glutathione (GSH) stability, intrinsic reactivity assays, and covalent docking (DOCKovalent, GOLD, HCovDock). Use when designing covalent inhibitors for targeted covalent inhibition (TCI), KRAS G12C-style approaches, or rationalizing covalent SAR.

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。

GPTomics/bioSkills1,2232026年8月15日 更新

Designs PROTACs, molecular glues, and bivalent degraders with explicit handling of E3 ligase choice (VHL, CRBN, IAP, MDM2, KEAP1), linker design (length, composition, rigidity), ternary complex prediction (PRosettaC, DeepTernary, AlphaFold3), cooperativity (alpha), DC50 / Dmax characterization, hook effect, and prediction-experiment reconciliation. Use when designing targeted protein degraders, planning linker SAR, predicting ternary complex stability, or building generative degrader workflows.

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。

GPTomics/bioSkills1,2232026年8月15日 更新

Review TDesign Flutter 组件的公开 Demo、API 收敛、Flutter 设计模式、主题、测试和 Golden 证据。以小程序公开 Demo 作为可见效果参考,但不机械映射其 props/events;适用于组件对齐和 PR 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。

Tencent/tdesign-flutter1,2162026年10月17日 更新

TDesign Flutter 通用协作约定,适用于仓库开发和 PR 工作,涵盖 Spec、更新日志、公开契约、生成产物、双版本及 CI 登记。组件对齐由 Review skill 补充,CNB 平台限制见仓库协作说明。

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。

Tencent/tdesign-flutter1,2162026年10月17日 更新

Apply Swift API Design Guidelines to name, label, and document Swift APIs. Covers argument label rules (prepositional phrase rule, grammatical phrase rule, first-label omission), mutating/nonmutating pair naming (-ed/-ing participle pattern, form- prefix, sort/sorted, formUnion/union), side-effect naming (noun for pure, verb for mutating), documentation comment structure (summary by declaration kind, O(1) complexity rule), clarity at call site, role-based naming, protocol naming (-able/-ible/-ing), default arguments over method families, casing conventions, and terminology. Use when designing new Swift APIs, reviewing naming and argument labels, writing documentation comments, or refactoring for call site 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。

dpearson2699/swift-ios-skills1,2102026年8月1日 更新

Use for new frontend applications, dashboards, games, creative websites, hero sections, and visually driven UI from scratch, or when the user explicitly asks for a redesign/restyle/modernization. Builds from clean, airy, high-taste, readable image-generated concept design with section-specific references, faithful implementation, and browser testing.

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。

fcakyon/claude-codex-settings1,1812026年10月16日 更新

Use when designing a Digital Down Converter (DDC) using dsphdl System objects. Triggers on requests involving DDC design, frequency down-conversion for FPGA/ASIC, NCO + mixer + decimation filter chains, fractional/non-integer sample rate conversion, or HDL-optimized receiver front-end signal processing.

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。

matlab/matlab-agentic-toolkit1,1772026年10月14日 更新

Cascade PCB components, add lumped elements, export Touchstone, and bridge to eye diagram or antenna array workflows. TRIGGER: user asks to cascade or connect multiple RF PCB components, add lumped R/L/C, export S-parameters to Touchstone, or combine PCB elements into a circuit. Invoke BEFORE writing pcbcascade or circuit code — cascade rules and port matching are non-obvious. SKIP: designing individual components (use the specific matlab-design-pcb-* skill), EM analysis of a single component (use matlab-analyze-em), material/stackup setup only (use matlab-manage-pcb-material), optimization (use matlab-optimize-pcb-design).

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。

matlab/matlab-agentic-toolkit1,1772026年10月14日 更新

Wilkinson, branchline, ratrace, directional couplers, corporate dividers, Rotman lenses for power splitting and beam-forming. TRIGGER: user asks to design, create, or analyze any coupler, splitter, power divider, combiner, or Rotman lens. Invoke BEFORE writing code — class names and design() availability vary per coupler type. SKIP: EM simulation/S-parameter extraction of an existing component (use matlab-analyze-em), building custom non-catalog geometry (use matlab-assemble-pcb-layout), material/stackup setup only (use matlab-manage-pcb-material), cascading multiple components (use matlab-integrate-pcb-circuit).

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。

matlab/matlab-agentic-toolkit1,1772026年10月14日 更新

Model a Phase-Locked Loop (PLL) IC from its datasheet or system specs using Mixed-Signal Blockset. Without this skill, agents universally select the wrong solver and produce non-functional PLL models — 100% of unguided attempts fail. Covers Integer-N, Fractional-N, Dual Modulus architectures, loop filter design, lock time optimization, VCO phase noise configuration, and msbPllArchitectures/msbPllFoundation block assembly. Use when: PLL modeling, frequency synthesizer design, phase noise simulation, lock time analysis, charge pump design, loop filter tuning, datasheet-to-model, Mixed-Signal Blockset PLL, msbPllArchitectures.

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。

matlab/matlab-agentic-toolkit1,1772026年10月14日 更新

Via modeling: pads, antipads, ground return vias, GRV placement, and signal integrity for high-speed layer transitions. TRIGGER: user asks to model a via, design a via transition, place ground return vias, analyze via performance, or check signal integrity through layer transitions. Invoke BEFORE writing code — only viaSingleEnded exists (no viaDifferential), and the location format is non-obvious. SKIP: general signal integrity without vias (use matlab-analyze-em), transmission line design (use matlab-design-pcb-transmission-line), PDN analysis (use matlab-analyze-pcb-pdn), material/stackup setup only (use matlab-manage-pcb-material).

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。

matlab/matlab-agentic-toolkit1,1772026年10月14日 更新

Microstrip, stripline, CPW, differential pairs, and crosstalk analysis for impedance-controlled PCB interconnects. TRIGGER: user asks to design or analyze a transmission line (microstrip, stripline, CPW, coplanar, differential pair), extract RLGC or per-unit-length parameters, compute trace impedance, analyze a PCB trace cross-section, or perform crosstalk/coupling analysis. Invoke BEFORE writing code — preferred over RF Toolbox analytical functions (txlineMicrostrip, txlineStripline, txlineCPW). SKIP: EM simulation/S-parameter extraction of an existing component (use matlab-analyze-em), material/stackup definition only (use matlab-manage-pcb-material), building custom non-catalog geometry (use matlab-assemble-pcb-layout), optimization sweeps (use matlab-optimize-pcb-design).

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。

matlab/matlab-agentic-toolkit1,1772026年10月14日 更新

Design and validate digital filters in MATLAB. Use when cleaning up noisy signals, removing interference, filtering signals, designing FIR/IIR filters (lowpass/highpass/bandpass/bandstop/notch), or comparing filters in Filter Analyzer.

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。

matlab/matlab-agentic-toolkit1,1772026年10月14日 更新

Build MATLAB apps from requirements to working code. Asks discovery questions (or skips them when the path is known), recommends UIFigure or UIHTML architecture, identifies layout archetype (Dashboard, Explorer, Tabbed, Wizard, Canvas), produces an implementation plan, and executes the build. For UIFigure apps, optionally serializes as App Designer (.mlapp or plain-text .m + .xml). Use when a user wants to build a MATLAB app, create a GUI, make an interactive tool, build a uifigure app, build a uihtml app, build an App Designer app, build a .mlapp app, build a plain-text App Designer app, or asks which approach to use. Also use when user describes spatial layout needs: dashboard, control panel, sidebar, tabs, wizard, stepper, canvas, workspace.

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。

matlab/matlab-agentic-toolkit1,1772026年10月14日 更新