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概要と使いどころ

Generates complete programmed-cell-death (PCD) / regulated-cell-death (RCD) bulk-transcriptome oncology research designs from a user-provided disease and mechanism theme. Always use this skill whenever a user wants to design, plan, or structure a cancer bioinformatics study built around cell-death patterns, tumor microenvironment, prognostic modeling, immune landscape analysis, mutation profiling, and computational drug sensitivity. Covers five study patterns (mechanism-gene-set, subtype-discovery, prognostic-signature, immune-response stratification, translational drug-hypothesis) 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, and a strictly verified reference literature retrieval layer with real references only.

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。

aipoch/medical-research-skills1,9542026年9月17日 更新

Generates complete reference-grounded single-drug adverse-effect network-pharmacology research designs from a user-provided drug, adverse event, and desired evidence depth. Always use this skill when a user wants to design, plan, or upgrade a conventional network-pharmacology study centered on one fixed drug and one fixed adverse-effect endpoint, using drug-target prediction, adverse-event target collection, overlap analysis, PPI hub prioritization, enrichment interpretation, molecular docking, and optional orthogonal transcriptomic or literature validation. Covers five study patterns (canonical hub-first, cardiotoxicity or electrophysiology-oriented, immune-inflammatory adverse effect, organ-toxicity pathway context, translational validation) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with a recommended primary plan, dependency/evidence map, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, verified-reference pack, and self-critical 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。

aipoch/medical-research-skills1,9542026年9月17日 更新

Use this skill to compute ESTIMATE immune-related microenvironment scores from a bulk expression matrix, generate an ESTIMATE score heatmap, and optionally generate group-wise ESTIMATE score boxplots plus significance tables when a sample group file is supplied. Trigger keywords: ESTIMATE, immune score, stromal score, tumor microenvironment score. NOT for: immune cell deconvolution, single-cell analysis, differential expression, clinical diagnosis.

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。

aipoch/medical-research-skills1,9542026年9月17日 更新

metronome

無料

Guides Metronome usage-based billing integration decisions — event ingestion (single and batch, idempotency, billable metrics), contract design (rate cards, overrides, dimensional pricing, products), invoicing lifecycle (grace periods, finalization, Stripe sync), credit and commit management (prepaid, postpaid, thresholds, auto-recharge), and Stripe integration (arrears invoicing, tax providers, line item limits). Use when building, modifying, or reviewing any Metronome integration — including ingesting usage events, creating customers, contracts, or rate cards, designing billable metric group keys, managing credits and commits, configuring invoicing, syncing invoices with Stripe Billing, billing AI applications for token usage, setting up self-serve (PLG) pricing, reviewing customer health, commit burn, portfolios, or renewals, or migrating from Stripe Billing Meters to Metronome.

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。

stripe/ai1,9412026年10月15日 更新

design-qa

無料

Set up or run design QA gates — token + hardcoded-value lint, automated a11y (axe), contrast, visual regression across variants/states/themes/RTL, and the manual a11y checklist. Use when the user wants CI quality gates, to prevent design regressions, or to QA a component/screen before shipping.

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。

plugin87/ux-ui-agent-skills1,7362026年10月11日 更新

Lookup documented AKS fixes only when the prompt includes an exact catalog signature and all of its qualifiers: VMCannotFitEphemeralOSDisk; NodePoolMcVersionIncompatible; 'NodeImageVersion is not accepted'; AKS SkuNotAvailable with size, location, and zone; ZonalAllocationFailed with insufficient zone capacity; OverconstrainedAllocationRequest with listed constraints; nested AKS vmssCSE/CSE VMExtensionError_OutboundConnFail, VMExtensionError_K8SAPIServerConnFail, or VMExtensionError_K8SAPIServerDNSLookupFail; or AllocationFailed with the full cataloged internal-error or insufficient-regional-capacity message. Never use for quota errors, code-only or bare wrappers, generic symptoms, incomplete signatures, or failures outside AKS; use aks-troubleshooting or azure-diagnostics.

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/azure-skills1,5712026年10月14日 更新

Design and build a 10-30 second motion-design showreel or brand reel in the style of Nate's Opus 5.5 "CLAUDE / MOTION REEL": one brand motif transformed through labeled craft chapters, a persistent HUD, cuts locked to a 120-130 BPM grid, a sub-second flurry, and a held logo lockup that answers the opening. Use when asked for a showreel, sizzle reel, brand reel, motion reel, "a reel like the Opus one", "show off motion design for <brand>", a 15-second brand film cut to music, or to study why a reference reel works and rebuild that energy for another brand.

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。

nateherkai/herk-edit-kit1,4822026年10月14日 更新

Design and build a 10-30 second motion-design showreel or brand reel in the style of Nate's Opus 5.5 "CLAUDE / MOTION REEL": one brand motif transformed through labeled craft chapters, a persistent HUD, cuts locked to a 120-130 BPM grid, a sub-second flurry, and a held logo lockup that answers the opening. Use when asked for a showreel, sizzle reel, brand reel, motion reel, "a reel like the Opus one", "show off motion design for <brand>", a 15-second brand film cut to music, or to study why a reference reel works and rebuild that energy for another brand.

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。

nateherkai/hyperframes-student-kit1,4822026年10月13日 更新

Builds and ships iOS/macOS apps with XcodeGen, SwiftUI and SPM: Xcode build fixes, device deployment, Apple Developer signing/notarization, CI/CD pipelines. Use for XcodeGen project.yml setup, "Library not loaded @rpath" crashes, code-signing errors (Error -25294, adhoc fallback), or Electron notarization failures. Not for TCC permission dialogs (use macos-permissions) or disk cleanup (use macos-cleaner).

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。

daymade/claude-code-skills1,4632026年10月14日 更新

Audits already-rendered UI and Markdown/Obsidian image layout — web app, deck/slide, dashboard, design-system, or Electron/native app — via real-browser/native-app journeys and a Playwright sweep. Use after UI implementation to find typography, overflow, responsive, routing, data-viz, browser-output, or native-shell defects, or to compare a render against a reference. Not for greenfield UI design (use ui-designer) or QA-program setup (use qa-expert).

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。

daymade/claude-code-skills1,4632026年10月14日 更新

Fix a team's chat sprawl — the channel map with one purpose per channel, the naming scheme that makes purpose findable, the archive pass for the dead and duplicated, and the posting norms (threads, @-discipline, urgency signals) that keep signal findable. Use when asked clean up our Slack/Teams, we have 90 channels and nothing is findable, set channel norms, or where should things get posted. Produces the channel audit and map, the naming scheme, the norms card, and the archive pass.

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。

mohitagw15856/pm-claude-skills1,4552026年10月13日 更新

Design a budget-vs-actuals tracker that stays alive past February — the category grain that matches real statements, the variance view that answers 'are we okay', the update ritual small enough to survive, and the honest handling of irregular expenses. Use when asked build me a budget spreadsheet, track team spend against budget, why do we always blow the budget invisibly, or design a household/project budget tracker. Produces the tracker structure, the variance logic, the irregulars ledger, and the monthly fifteen-minute ritual.

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。

mohitagw15856/pm-claude-skills1,4552026年10月13日 更新

Audit the beneficiary designations that quietly override wills — the account-by-account sweep, the life-event triggers that make them stale, and the coordination check against actual intentions. Use when asked check my beneficiaries, does my 401k go to my ex, do beneficiary forms beat a will, or what should I update after marriage/divorce/a birth. Produces the account sweep list, the stale-designation red flags, the intent-vs-paperwork comparison table, and the update checklist with the verify-in-writing step.

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。

mohitagw15856/pm-claude-skills1,4552026年10月13日 更新

Modular design, interface stability, dependency management, AI-code health. Triggers: architecture, design, structure, modules, dependencies, coupling, system 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。

hashgraph-online/awesome-codex-plugins1,3172026年10月14日 更新

mailagent

無料

Temporary inboxes for agent signup QA — create disposable addresses, wait for verification email, extract OTP or magic links. Use when automating signup, login, or email verification without parsing HTML manually.

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。

hashgraph-online/awesome-codex-plugins1,3172026年10月14日 更新

Use the `sendsets` CLI to drive SendSets as a signed-in user - sign in with `sendsets login`, run `sendsets doctor`, then connect the app (`connection`), add or test mailboxes and their warmup (`mailbox`), send product events (`events send`), and build, validate, test and launch campaigns, including app_action and wait_for_event steps, on the hosted service or any self-hosted instance. Use whenever the task is to set up or operate SendSets from a terminal or a script and a `sendsets` binary is available, with no dashboard. For instance recovery and accounts (database-level), use sendsets-ops 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。

hashgraph-online/awesome-codex-plugins1,3172026年10月14日 更新

Reapply and repair Windows Codex Desktop after Store upgrades, including custom provider models hidden by Statsig available_models filtering, the dependent blue-purple Power slider and its Ultra toggle, Fast Mode request/UI gates, locale i18n, plugin UI gates, Chrome/browser_use gates, Goal command gates, Windows Computer Use availability gates and plugin/runtime repair, phone remote-control pairing under third-party/API-key main app usage, Desktop dynamicTools/inputSchema thread-start schema drift, local conversation visibility recovery after model_provider switches, restored-conversation missing-cwd continuation repair, ASAR integrity repair, signing/installing patched MSIX packages, SDK cleanup, Fast Mode wire verification, local plugin marketplace registration, and optional custom model_instructions_file setup (the bundled system prompt, also called 听话水).

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。

chen0416ccc-cpu/codex-windows-fast-patch-skill1,2792026年10月12日 更新

Generate a single photoreal or designed image with OpenAI gpt-image via fal.ai. Supports gpt-image-1 (default, fixed sizes — the FAL fallback for Higgsfield's `gpt_image_2`) and gpt-image-2 (`openai/gpt-image-2`, custom output sizes up to 3840px). Routes to text-to-image or the edit variant depending on whether a reference image is provided. Use for photoreal character anchors, scene keyframes, and designed sheets (e.g. storyboards) where precise layout and legible text matter.

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。

gooseworks-ai/goose-skills1,2522026年10月14日 更新

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-fabric1,2502026年10月5日 更新

Basecalls raw Oxford Nanopore signal (POD5/FAST5) into reads with Dorado, choosing the chemistry-matched model and accuracy tier (fast/hac/sup), requesting modified bases (5mCG_5hmCG, 6mA, m6A) at basecall time, and handling duplex, demultiplexing, trimming, and HERRO read correction. Covers why the model+version is an irreversible analysis decision, why methylation cannot be recovered later, and why downstream polish/variant models must match the basecaller. Use when converting POD5/FAST5 to reads, picking a Dorado model for R9/R10 or RNA004, enabling methylation calling, basecalling duplex, demultiplexing barcoded runs, or correcting reads for assembly.

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 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

Detects m6A modifications from Oxford Nanopore direct-RNA-seq (DRS) signal using m6Anet (multiple-instance-learning over DRACH 5-mer signal). Covers the upstream pipeline (Dorado/Guppy basecalling -> minimap2 map-ont -> nanopolish eventalign -> m6anet dataprep -> m6anet inference), per-site vs per-read probability including the mod_ratio stoichiometry column, the DRACH-only constraint, minimum-coverage thresholds (20-50 reads/site), multi-condition comparison via xPore/Nanocompore/ELIGOS, Dorado native modification calling (RNA004, 2024+), and the cDNA-vs-DRS distinction (cDNA Nanopore CANNOT detect modifications). Use when calling m6A from ONT DRS without immunoprecipitation, choosing m6Anet vs xPore vs Nanocompore vs ELIGOS vs Dorado native, interpreting probability_modified vs mod_ratio vs per-read probabilities, deciding between m6Anet (known DRACH sites) and Dorado/Remora (genome-wide screening), pinning RNA002 vs RNA004 chemistry and basecaller versions, or troubleshooting eventalign/dataprep failures.

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

Analyzes differential transcript usage (DTU) and isoform switches with functional consequence prediction (NMD via 50nt rule, ORF disruption, protein domain loss/gain, signal peptide changes, IDR alterations, coding-potential shifts). Tools include IsoformSwitchAnalyzeR v2 (auto-selects satuRn for >5 reps else DEXSeq), the manual DRIMSeq -> DEXSeq/satuRn -> stageR DTU pipeline, and fishpond/swish for inferential-uncertainty-aware DTE. Distinguishes DTU from DGE and DTE; integrates external annotators (CPC2, Pfam, SignalP, IUPred2A or DeepTMHMM). Use when investigating how splicing differences alter protein function or trigger NMD-mediated degradation.

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

onboarding workflow for creating datasets and applications in Viking AI Search. Supports one-time import from local files (JSON, JSONL, CSV) and MySQL databases, plus scheduled incremental sync for append-only JSONL files and MySQL. All sources are first exported to a bootstrap JSONL file; backend-driven schema inference handles detection, and optional background sync keeps the dataset up to date as new data arrives.

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。

volcengine/SearchCLI1,1882026年10月14日 更新