2.3万 件 ・ 関連度順
概要と使いどころ
Manages Fabric Variable Library items, including definitions, libraryVariables and valueSets overrides. Covers which consumers can reference a variable and with what syntax -- pipelines, notebooks via notebookutils variableLibrary, Dataflow Gen2, Copy Jobs, shortcuts, UDFs and Plan items -- the active value set per workspace or deployment stage, and Git serialization for CI/CD.
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Handles BED-format genomic intervals (BED3 through BED12, narrowPeak/broadPeak) and the coordinate-system substrate the whole interval category rests on, with bedtools (CLI) and pybedtools/pyranges/pandas (Python). Covers the 0-based half-open vs 1-based-closed convention boundary and the start-1/end-unchanged conversion, the silent failures (chrom-name mismatch, CRLF, lexicographic-vs-version sort under -sorted), genome/chrom.sizes generation, sorting contracts, BED12 block invariants, validation, makewindows, cross-assembly liftover (liftOver/CrossMap), and BED<->VCF/BAM/FASTA conversion. Use when reading, creating, validating, sorting, lifting between genome builds, or converting interval files, preparing inputs for bedtools/tabix/bigBed, or debugging an off-by-one or empty-overlap result.
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Analyzes base-editing screens for variant function. Covers library design (Hanna 2021 ClinVar-scale CBE screen benchmarked on BRCA1/2, Cuella-Martin 2021 DDR saturation), CBE vs ABE chemistry choice (BE3/BE4 vs ABE7.10/ABE8.20/ABE8e), editing-window math (positions 4-8 from PAM-distal end; 4-7 for ABE7.10), bystander-edit quantification and the variant-call ambiguity it creates, sgRNA-efficiency filtering before hit calling, indel byproduct interpretation, the substitution-vs-indel diagnostic, variant annotation against ClinVar / COSMIC, and the Broad be-validation-pipeline. Use when designing a BE variant screen, choosing CBE vs ABE for a specific edit, interpreting bystander-confounded hits, distinguishing functional signal from indel artifact, integrating CRISPResso2 output with screen scoring, or deciding BE vs PE for SNV installation.
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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.
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Predicts whether a DNA variant alters mRNA splicing using sequence-based deep-learning tools — SpliceAI (10kb context dilated CNN, clinical default), Pangolin (multi-tissue), MMSplice (modular per-region CNN with calibrated ΔPSI), SpliceTransformer/TrASPr (tissue-aware transformers), SpliceVault (empirical 300K-RNA lookup of likely mis-splicing outcomes), CADD-Splice (composite score). Applies the ClinGen SVI 2023 framework for ACMG/AMP variant interpretation (PVS1, PP3, BP4 evidence codes), HGVS splicing nomenclature (c.123+1G>A, c.123-3T>G, r.spl?), extended-window scoring for deep-intronic pseudoexons, tissue-specific predictions, branchpoint variant detection (BPHunter, LaBranchoR), and splice-switching ASO design. Use when interpreting splice impact of clinical variants, prioritizing VUS, identifying deep-intronic pathogenic variants, or designing ASOs.
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Use when the user needs to design evaluation datasets, create test cases, stratify samples, generate adversarial examples, extract eval dimensions from traces/specs, or build a labeled evaluation set. Also use when the user mentions test data design, eval coverage, difficulty stratification, synthetic data generation for eval, or "how to create good evaluation data." Outputs datasets in OpenJudge-compatible format.
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Use when the user has a RAG (Retrieval-Augmented Generation) system and wants to evaluate its quality — separating retrieval issues from generation issues. Also use when the user mentions RAG evaluation, faithfulness checking, hallucination detection in RAG, retrieval quality, chunking optimization, or "is my RAG pipeline working." Outputs a diagnostic matrix that pinpoints whether problems are in retrieval or generation.
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When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," "new user experience," "users aren't activating," "nobody completes setup," "low activation rate," "users sign up but don't use the product," "time to value," or "first session experience." Use this whenever users are signing up but not sticking around. For signup/registration optimization, see signup. For ongoing email sequences, see emails.
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When you want to brainstorm and check available .com domains for a new project — brand naming, aftermarket pricing (HugeDomains / Afternic / Sedo / Dan), USPTO trademark screening, and social handle availability. Built on Laura Roeder's "work backwards from availability" method. Combines Vercel CLI, whois, Domainr, Namecheap, and agent-browser, each for what it reliably does. Workflow: budget → brainstorm → availability check → whois cross-check → price → aftermarket sweep (plus liveness probe and drop-watch) → bucket → negotiate → trademark + socials → buy. Triggers on "/domain," "find a domain," "check domain availability," "brainstorm a domain," "what .com is available for X," "domain hunt," "name my project," "is X.com available," "aftermarket price on X.com," "trademark check for X."
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Bo tai lieu ban hang cong voi ky luat giu pipeline cho SME VN, gop mot skill vi cung mot nguoi lam ca hai viec — the persona nguoi mua (co ca nguoi can duong), one-pager, outline bo slide tu van, thu vien xu ly phan doi kieu VN viet o hai dang (bang tra nhanh khi dang goi va ban day du de dao tao), kich ban demo co moc thoi gian, bao gia, giai doan pipeline co tieu chi RA cong nguoi chiu trach nhiem cong SLA, quy tac toc do phan hoi inbox Zalo, va phuong an khong co CRM bang Google Sheet cong nhan Zalo. Kich hoat khi user nhac 'tai lieu ban hang', 'sales deck', 'xu ly phan doi', 'kich ban tu van', 'pipeline ban hang', 'quan ly khach tiem nang', 'bao gia cho khach', 'khach noi de suy nghi them'. Khong dung cho — tim va tao lead moi thi dung skill 33-b2b-lead-gen; thiet ke goi ban va muc gia thi dung skill 31-offer-design va skill 17-pricing-strategy.
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Dung khi can hieu VI SAO nguoi ta mua va ap dung nguyen tac tam ly vao marketing — khan hiem, bang chung xa hoi, cam ket nhat quan, uy tin, co lai, neo gia, ac cam mat mat — kem cach dua vao copy, landing page, email, ads va dieu chinh theo van hoa Viet Nam. Kich hoat khi user nhac 'tam ly khach hang', 'marketing psychology', 'FOMO', 'social proof', 'khan hiem', 'Cialdini', 'lam sao thuyet phuc khach', 'trigger cam xuc', 'khach doc xong van khong hanh dong'. Khong dung cho — viet copy thanh pham thi dung skill 05-copy-quang-cao; dong goi goi ban va bonus thi dung skill 31-offer-design; chan doan mot trang cu the khong ra don thi dung skill 68-cro-audit-trang.
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Scaffolds eval.yaml evaluation specs for skills, custom agents, and redistributable gh-aw workflow packages in the dotnet/skills repository. Use when creating skill or workflow-package tests, writing evaluation stimuli, defining graders and rubrics, sizing an eval for statistical power, or setting up test fixture files. Handles the Vally eval.yaml schema, fixture organization, and overfitting avoidance. Do not use for running or debugging existing evals (use improve-skill-quality) nor for skills authoring (use create-skill).
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Use when you need to implement or improve Java metrics observability with Micrometer — including meter design, naming/tag conventions, cardinality control, timers/counters/gauges/distribution summaries, percentiles/histograms, Actuator/Prometheus integration, and metrics validation through tests. This should trigger for requests such as Improve metrics; Apply Micrometer; Add metrics observability; Refactor Micrometer instrumentation; Add Micrometer timers counters or gauges to Java services. Part of Plinth Toolkit
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Use when you need to generate a checklist document with Java system prompts from skills.xml, following the embedded section template and producing INVENTORY-SKILLS-JAVA.md. This should trigger for requests such as Create Java system prompts checklist; Generate INVENTORY-SKILLS-JAVA.md; Use @003-skills-inventory; Inventory Java cursor rule skills; List available Java system prompt skills. Part of Plinth Toolkit
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Use when you need to apply data-oriented programming best practices in Java — including separating code (behavior) from data structures using records, designing immutable data with pure transformation functions, keeping data flat and denormalized with ID-based references, starting with generic data structures converting to specific types when needed, ensuring data integrity through pure validation functions, and creating flexible generic data access layers. This should trigger for requests such as Improve the code with Data-Oriented Programming; Apply Data-Oriented Programming; Refactor the code with Data-Oriented Programming; Model Java data with records and pure functions; Separate Java behavior from immutable data structures; Validate data integrity with pure Java functions. Part of Plinth Toolkit
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Use when you need to implement acceptance tests from maintainer-sanitized Gherkin scenario facts for framework-agnostic Java (no Spring Boot, Quarkus, Micronaut) — confirming @acceptance scenarios before coding, happy path with RestAssured, DB/Kafka test fixtures, WireMock for external REST only, and *AT classes run by Failsafe. This should trigger for requests such as Review Java code for acceptance tests; Apply best practices for acceptance tests in Java code; Implement acceptance tests from Gherkin scenarios in Java; Map feature files to Java step definitions; Review Cucumber acceptance tests for Java services. Part of Plinth Toolkit
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Use when you need to review, improve, or write Java unit tests — including migrating from JUnit 4 to JUnit 5, adopting AssertJ for fluent assertions, structuring tests with Given-When-Then, ensuring test independence, applying parameterized tests, mocking dependencies with Mockito, verifying boundary conditions (RIGHT-BICEP, CORRECT, A-TRIP), leveraging JSpecify null-safety annotations, or eliminating testing anti-patterns such as reflection-based tests or shared mutable state. This should trigger for requests such as Review Java code for unit tests; Apply best practices for unit tests in Java code; Write fast JUnit unit tests for Java code; Improve Mockito-based Java unit tests; Refactor Java tests to isolate collaborators. Part of Plinth Toolkit
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Integration skill for Lovable.dev projects. Activates when working with: - Lovable.dev projects with GitHub sync - Supabase Edge Functions that need deployment - Database migrations for Lovable Cloud - Projects with supabase/ directory structure - Any mention of "Lovable", "deploy edge function", "apply migration" Provides exact Lovable prompts for backend operations that can't be done via GitHub alone.
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Maps the US federal privacy landscape including sectoral laws (HIPAA, GLBA, FERPA, COPPA, FCRA, ECPA, VPPA), FTC Section 5 enforcement, proposed federal comprehensive legislation, and the interaction between federal and state privacy regimes. Keywords: federal privacy, HIPAA, GLBA, FERPA, COPPA, FCRA, FTC, sectoral, preemption.
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Vendor certification acceptance criteria and equivalence mapping. Covers ISO 27701, SOC 2 Privacy, APEC CBPR, EU Code of Conduct evaluation, certification scope analysis, gap supplementation requirements, and cross-framework equivalence assessment.
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Guides privacy program effectiveness measurement including leading and lagging indicators, KPI definition, benchmarking methodology, executive reporting formats, board-level privacy dashboards, and metric-driven program improvement. Covers operational, compliance, risk, and strategic privacy metrics across the program lifecycle. Keywords: privacy metrics, KPIs, benchmarking, executive reporting, dashboard, program effectiveness.
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Guides implementation of the NIST Privacy Framework IDENTIFY function covering ID.BE business environment, ID.DA data actions, ID.IM improvement, and ID.RA risk assessment subcategories. Maps NIST PF controls to GDPR requirements for dual-framework compliance. Keywords: NIST Privacy Framework, IDENTIFY function, ID.BE, ID.DA, ID.IM, ID.RA, privacy risk assessment, data actions.
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Guides privacy program maturity assessment using the AICPA/CIPT Privacy Maturity Model with five levels: Ad Hoc, Repeating, Defined, Managed, and Optimized. Covers assessment methodology across ten privacy domains, scoring criteria, gap analysis, maturity roadmap generation, and benchmarking against industry peers. Keywords: privacy maturity, AICPA, maturity model, assessment, roadmap, benchmarking.
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Guides the Privacy Threshold Analysis screening process to determine whether a full DPIA is required. Provides a quick-screen questionnaire, threshold criteria based on WP248rev.01, escalation triggers, and documentation requirements. Activate when evaluating new processing activities, system changes, or procurement decisions. Keywords: PTA, privacy threshold analysis, DPIA screening, quick-screen, threshold criteria, WP248, escalation triggers.
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