Azure Event Grid SDK for .NET. Client library for publishing and consuming events with Azure Event Grid. Use for event-driven architectures, pub/sub messaging, CloudEvents, and EventGridEvents.
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概要と使いどころ
Azure Event Grid SDK for .NET. Client library for publishing and consuming events with Azure Event Grid. Use for event-driven architectures, pub/sub messaging, CloudEvents, and EventGridEvents.
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。
Deploy web apps with backend APIs, database, and file storage. Use when the user asks to deploy or publish a website or web app and wants a public URL. Uses HTTP API via curl.
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会話の文脈をHTMLとMarkdownのプレビューサイトとして公開するときに使用する。
E-commerce product-management desk (Busabase App-in-Skill) for catalog master data, SKUs, pricing, inventory, channel status, content assets, compliance notes, lifecycle state, and approval-gated product operations. Use when the user invokes $kelly-products or /kelly-products, asks for 电商商品管理, 商品库, SKU 管理, inventory/reorder, product status across Amazon/Shopify/TikTok Shop/eBay, channel publishing approvals, price-change review, quality holds, product lifecycle/archive decisions, or a Busabase-backed product management desk.
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Repurpose source content into channel-ready drafts with a Busabase App-in-Skill review and export workflow. Use when the user asks to write content, make a content pack, turn a main blog/long article/transcript/notes into Xiaohongshu, WeChat, newsletter, LinkedIn, X/Twitter, short video scripts, SEO snippets, or a multi-platform publishing plan; also use when they ask for a content approval dashboard or App-in-Skill content workflow.
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Natural, identity-preserving portrait retouching with a local CLI and a Busabase-backed review app. Use when the user asks to 美颜, 修人像, 磨皮, 提亮肤色, portrait retouch, headshot cleanup, profile-photo polish, before/after comparison, or batch portrait enhancement. Default to local non-destructive processing, preserve facial structure and skin texture, and require explicit approval before replacing or publishing any image.
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Read, answer and post on the Sandock community forum at community.sandock.ai through its /api/v1/community REST API. Lists categories and posts, reads a thread with its replies, searches, and publishes posts and replies behind an explicit confirmation. Use when the user invokes $sandock-community or /sandock-community, asks what is happening in the Sandock community, wants an unanswered question triaged or answered, or wants something posted or announced there.
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。
Read, answer and post on the Buda community forum at community.buda.im through its /api/v1/community REST API. Lists categories and posts, reads a thread with its replies, searches, and publishes posts and replies behind an explicit confirmation. Use when the user invokes $buda-community or /buda-community, asks what is happening in the Buda community, wants an unanswered question triaged or answered, or wants something posted or announced there.
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。
Read, answer and post on the Busabase community forum at community.busabase.com through its /api/v1/community REST API. Lists categories and posts, reads a thread with its replies, searches, and publishes posts and replies behind an explicit confirmation. Use when the user invokes $busabase-community or /busabase-community, asks what is happening in the Busabase community, wants an unanswered question triaged or answered, or wants something posted or announced there.
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 publish-ready LinkedIn posts for B2B SaaS marketing leaders writing from an operator point of view: real decisions, real trade-offs, real constraints, and defensible lessons. Use when turning an internal observation, framework, campaign decision, miss, or shipped artifact into a public LinkedIn post. Best for demand generation, ABM, marketing ops, product marketing, and SaaS GTM leaders building credibility through practical operating insight. Not intended for generic brand posts, company announcements, sales outreach, or long-form content.
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Produces and audits externally published marketing copy where factual claims must survive scrutiny — landing pages, product pages, launch emails, one-pagers, search/social metadata. Every statistic, competitor comparison, capability description, and proof point is traced to a fetched source or the project's own documents, labeled, and adversarially verified before it ships. Use when writing or rewriting high-stakes marketing copy; when copy must pass legal, compliance, brand, or claims review; when the audience is skeptical technical or executive buyers; when the company has little or no customer proof yet (pre-launch, zero customers); or when auditing existing copy for unsupported claims, invented capabilities, unverified statistics, or AI-slop language.
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。
Deploy applications and infrastructure to Cloudflare using Workers, Pages, and related platform services. Use when the user asks to deploy, host, publish, or set up a project on Cloudflare.
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Turn the current conversation into a PRD and publish it to the project issue tracker — no interview, just synthesis of what you've already discussed.
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Take a markdown file of raw material and shape it into an article through a conversational session — drafting candidate openings, growing the piece paragraph by paragraph, arguing about format (lists, tables, callouts, quotes) at each step. Use when the user has a pile of notes, fragments, or a rough draft and wants help turning it into something publishable.
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Work safely with endpoint versions — preview a draft in the playground, roll back to an older version, update settings on one version without bumping query history, deactivate a specific version. Use when the user asks "how do I roll back my endpoint", "preview my changes before publishing", "I want to fix v5 without bumping the version", or anything involving the version history. Calls out today's limitations honestly: there is no pointer flip; "rollback" means forking the old query into a new top version.
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Rigorous methodology for evaluating ML models on established benchmarks. Covers proper train/val/test splits, baseline verification from original papers, exact metric formula discrepancies, data-leak detection checklist, multi-seed robustness, and honest reporting templates. Use when claiming to beat published baselines, writing methods papers, or auditing existing results.
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Selects biomarker features from high-dimensional omics data using Boruta all-relevant selection, mRMR, LASSO/elastic-net, and stability selection, while controlling the leakage, irreproducibility, and correlated-feature traps that make most published signatures fail to replicate. Use when identifying candidate biomarkers, deciding between an all-relevant and a minimal-optimal selector, or judging whether a selected gene set is reproducible. For unbiased performance estimation of the resulting model see machine-learning/model-validation; for interpreting a trained model see machine-learning/prediction-explanation.
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Authors reproducible Nextflow DSL2 pipelines built on reactive dataflow, where processes communicate only through channels and execution order is not guaranteed. Use when deciding channel/dataflow (Nextflow) vs rule-based (Snakemake) authoring; wiring queue vs value channels and fixing shared-reference exhaustion with .first(); composing DSL2 modules and subworkflows with take/main/emit; selecting container/conda profiles and pinning images by digest for portability across local/SLURM/LSF/AWS Batch/Google Batch/Kubernetes executors; diagnosing why -resume misses the cache (nondeterministic input order, mtime on network filesystems, mutable :latest tags) with cache 'lenient' and -dump-hashes; managing work/ vs publishDir and dynamic retry escalation; and choosing whether to adopt an nf-core community pipeline or author from scratch.
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ToolUniverse plugin router. STEP 1 BEFORE ANY ANALYSIS: if the data folder contains `*_executed.ipynb`, run `tu run read_executed_notebook '{"data_folder":"<path>","search":"<keyword>"}'` to extract its cell outputs and apply EVERY filter/sample-exclusion the notebook used — even when the question says 'Using DESeq2/Run X/Compute Y' (this describes the METHOD the notebook used, not a request to rerun). The notebook's cell outputs are the only published authoritative answers; reimplementing or reading stale pre-computed CSVs in the data folder produces different numbers because of outlier-sample removal, library version, and filter steps you don't see by skimming. STEP 2 routing — pick a sub-skill name from this exact list (never invent): tooluniverse-rnaseq-deseq2 (RNA/miRNA-seq DE, correlation, PCA, clustering, dispersion), tooluniverse-gene-enrichment (GO/KEGG/Reactome/GSEA/pathway enrichment), tooluniverse-statistical-modeling (regression, ANOVA, ordinal/logistic, chi-square, correlation, power), tooluniverse-image-analysis (microscopy, colony, fluorescence, dose-response, .tif — including ANOVA / Dunnett / power-analysis on image-derived measurements), tooluniverse-epigenomics (DNA methylation, CpG, m6A, MeRIP-seq, bisulfite, ChIP-seq, chromatin), tooluniverse-sequence-analysis (FASTQ, Trimmomatic, BWA, samtools, coverage), tooluniverse-variant-analysis (VCF, VAF, SNP, mutation), tooluniverse-phylogenetics (treeness, PhyKIT, parsimony), tooluniverse-single-cell (scRNA, h5ad, scanpy), tooluniverse-crispr-screen-analysis (MAGeCK, sgRNA), tooluniverse-proteomics-analysis (mass spec, TMT). Use for CSV/Excel/VCF/FASTA/h5ad and any biology/chemistry/medicine analysis question.
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Enzyme kinetics — Michaelis-Menten Km, Vmax, kcat (turnover), and kcat/Km (catalytic efficiency / specificity constant) from substrate-velocity data, plus inhibition-mechanism analysis (competitive / uncompetitive / non-competitive, Ki). Fits the MM equation by nonlinear regression (and reports Lineweaver-Burk for reference). Use when you have substrate concentrations and initial reaction velocities and need kinetic parameters or to classify an inhibitor. NOT for BRENDA database lookups of published constants (use the BRENDA tools).
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Resize and convert manuscript images to KDP-compliant dimensions at 300 DPI for print-on-demand.
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。
Starts a CARLA UE 5.8 server from a ue58-dev tree — the editor binary in -game mode (the working headless server), the packaged shipping build, or the full editor — with offscreen/nullrhi rendering, custom RPC and streaming ports, and native ROS 2 via the single-dash -ros2 flag. Probes a running server, and stops one cleanly despite the 15-character process-name truncation. Use when the user asks to "run/start CARLA UE5", "launch a ue58 server", "run headless", "publish ROS 2 topics from UE5", or a client cannot reach the simulator.
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Downloads CARLA so nothing has to be fetched by hand — an official release package for any published version (resolved live from the GitHub releases, with AdditionalMaps), the rolling nightly Dev build, a shallow source checkout of a branch or tag, or the carlasim/carla Docker image. Reports exactly what was obtained and where, plus the environment variables the other skills read. Use when the user asks to "download CARLA", "get CARLA 0.9.16", "install CARLA", "clone the carla repo", "fetch the latest CARLA", or has no CARLA at all yet.
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Queries the live CARLA world and resolves an entity description into a concrete actor id — find actors by type, role, or colour, or the single one nearest a point/actor; read the world snapshot; get static level bounding boxes by label; cast rays for semantic points; project a point to the ground; or (ros-topics) list the native ROS 2 topics each actor should be publishing and why any is silent. Identifies by stable attributes, not by any rank/order. Use when the user asks "what actors are here", "find the red prius", "the vehicle nearest the ego", "list the pedestrians", or needs a specific actor id for another 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。