「classification」の検索結果

Expert Australian Information Security Manual (ISM) advisor for government entities and their supply chains. Use for ISM control selection, gap analysis, system authorisation, IRAP assessment preparation, security documentation, and ASD compliance. Triggers on: ISM controls, ASD compliance, IRAP assessment, PROTECTED system scoping, Essential Eight vs ISM, system authorisation, NC/OS/ PROTECTED/SECRET/TOP SECRET classification markings, security objectives, ISM guidelines or chapters, control applicability markings, cybersecurity documentation for Australian government, and any question about the ASD Information Security Manual framework or Australian government cybersecurity obligations.

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Assess compliance with the EU General-Purpose AI (GPAI) Code of Practice under the AI Act (Regulation (EU) 2024/1689). Use when asked to determine GPAI model provider obligations, assess Code of Practice compliance, evaluate transparency or copyright requirements for GPAI models, check systemic risk obligations, build a GPAI compliance roadmap, or prepare for AI Office requests. Covers all three Code chapters (Transparency, Copyright, Safety & Security), the 12 commitments and their measures, systemic risk classification (Article 51), provider obligations (Articles 53 and 55), open-source exemptions, enforcement timeline, Commission/AI Office supervision, and DACH-specific overlays such as BSI cybersecurity and works council implications. Triggers on phrases like "GPAI compliance", "Code of Practice assessment", "GPAI model obligations", "systemic risk evaluation", "AI Act transparency requirements", "GPAI copyright policy", "general-purpose AI compliance".

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Expert DORA (Regulation (EU) 2022/2554 — Digital Operational Resilience Act) compliance advisor for EU financial entities. Use this skill whenever a user asks about DORA compliance, ICT risk management frameworks, ICT incident classification or reporting, threat-led penetration testing (TLPT), ICT third-party risk management, Register of Information, contractual provisions with ICT providers, ICT concentration risk, oversight of critical ICT third-party service providers (CTPPs), or any DORA RTS/ITS obligation. Also trigger for: "DORA gap analysis", "DORA readiness", "Art. 6 ICT risk framework", "Art. 17 incident reporting", "Art. 26 TLPT", "Art. 28 third-party policy", "Art. 30 contractual provisions", "Register of Information CIR 2024/2956", "critical TPSP designation", "DORA vs NIS2", "DORA simplified framework", or EBA/ESMA/EIOPA digital resilience guidance.

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Depth assessment of whether an AI system is high-risk under Art. 6 of the EU AI Act, grounded in the Commission's draft Art. 6(5) classification guidelines (general principles + Annex I + Annex III). Covers the Annex I product-safety route, all eight Annex III areas with worked examples, the Art. 6(3) exception and its profiling re-exception, and the Art. 25 quasi-provider trap. Outputs a structured decision block, a practitioner memo, and a JSON interchange artefact.

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。

Expert EU Cyber Resilience Act (CRA) advisor for Regulation (EU) 2024/2847 — mandatory cybersecurity and vulnerability handling requirements for all products with digital elements (PDEs) sold in the EU. Use this skill for gap analysis, product classification (Default / Class I / Class II), conformity assessment route selection, CE marking, SBOM requirements, vulnerability and incident reporting to ENISA/CSIRTs, support period obligations, and manufacturer/importer/distributor duties. Trigger for EU CRA, Cyber Resilience Act, PDE compliance, Annex I requirements, SBOM EU, CE marking cybersecurity, or connected product security EU.

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An end-to-end method for drafting and finalising a complex, multi-pillar regulated fintech agreement — from intake to signature. Authored from a senior fintech lawyer's manual: a licensed payment-services provider engaging a counterparty across agent cash-in/cash-out, QR payments, wallet e-payments, and a marketplace, each with its own regulatory profile. Runs five phases and fourteen steps: regulatory mapping (activity-to-licence matrix, grey-zone classification gates), architecture (framework-plus-sub-agreement structure, ring-fenced marketplace), the regulatory–commercial balance (what flexes vs what cannot), core drafting (authority, float mechanics, hard-coded regulator caps, liability — all tracking control), execution-blocker triage, and a pre-signature check closing open blockers as conditions precedent. It refuses to invent licence-specific values or draft a representation as true without executed evidence. Use it to structure, draft, negotiate, or review any regulated payments contract.

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。

EU Data Act (Regulation (EU) 2023/2854) skill for lawyers. Use when the user asks about Data Act classification, drafting, lookup, analysis, or audit. Triggers include "Data Act", "Regulation 2023/2854", "connected product", "related service", "data processing service", "DPS switching", "Article 3(2) pre-contract", "Article 25 contract", "trade-secret handbrake", "international government access", "Chapter VI cloud switching", "Article 50 timeline", "FAQ Q22a", "data holder", "exportable data", "functional equivalence", "Art. 4(10) competing product", and similar EU Data Act phrases. The skill produces lawyer-style Word output and cites verbatim from bundled regulation and FAQ source texts.

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California Consumer Privacy Act (CCPA) and California Privacy Rights Act (CPRA) compliance advisor — business threshold analysis, consumer rights fulfillment (access, delete, correct, opt-out of sale/sharing, limit SPI, ADMT opt-out), privacy notice drafting, service provider vs. contractor vs. third-party classification, sensitive personal information (SPI) handling, data minimization, opt-out mechanisms (including GPC), cybersecurity audits and risk assessments (live since Jan 1, 2026), ADMT obligations (effective 2026, deadline Jan 1, 2027), CPPA enforcement (Disney $2.75M, PlayOn $1.1M, Ford $375K), penalty exposure, GDPR comparison, and gap assessments for businesses operating in or targeting California residents.

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。

Use when a user asks what the EU Cyber Resilience Act (CRA) means for their product, whether and when they must report a vulnerability or incident, or what a specific CVE triggers legally. Maps a product with digital elements to CRA scope, product classification, Annex I vulnerability-handling duties, and Article 14 reporting obligations — every legal claim cited from official regulation text fetched live through the Ansvar Gateway MCP connector, joined with live CVE / CISA-KEV / EPSS vulnerability intelligence from the same connector.

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When you want to create, adapt, or update an Agent Skill (Claude Code, Codex, Cursor, and other hosts) in one of your repos (listed in ~/.config/makerskills/skillify/repos.yaml; defaults to makerskills). Modes — CREATE (from chat, video, dump, or scratch) turns a workflow into a new skill. ADAPT ports an external skill with keep/adapt/add classification, license check, and attribution. UPDATE improves existing skills from learnings with cross-skill propagation, memory-vs-skill triage, and semver. Checks new skills for host portability. Triggers on "/skillify," "create a skill," "make this a skill," "skill from this chat," "adapt this skill," "port this skill," "fork this skill," "update X skill," "apply this to the relevant skills," "propagate this learning," "improve [skill]," "fix [skill]." Part of the -ify trifecta (skillify / toolify / loopify).

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The ORFhunteR package is a R and C++ library for an automatic determination and annotation of open reading frames (ORF) in a large set of RNA molecules. It efficiently implements the machine learning model based on vectorization of nucleotide sequences and the random forest classification algorithm. The ORFhunteR package consists of a set of functions written in the R language in conjunction with C++. The efficiency of the package was confirmed by the examples of the analysis of RNA molecules fr

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。

We propose an Asymmetric Within-Sample Transformation (AWST) to regularize RNA-seq read counts and reduce the effect of noise on the classification of samples. AWST comprises two main steps: standardization and smoothing. These steps transform gene expression data to reduce the noise of the lowly expressed features, which suffer from background effects and low signal-to-noise ratio, and the influence of the highly expressed features, which may be the result of amplification bias and other experi

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。

A package for demultiplexing single-cell sequencing experiments of pooled cells labeled with barcode oligonucleotides. The package implements methods to fit regression mixture models for a probabilistic classification of cells, including multiplet detection. Demultiplexing error rates can be estimated, and methods for quality control are provided.

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Infrastructure to support 'views' used to classify Bioconductor packages. 'biocViews' are directed acyclic graphs of terms from a controlled vocabulary. There are three major classifications, corresponding to 'software', 'annotation', and '

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。

Expert knowledge for Azure AI Document Intelligence development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using AnalyzeDocument APIs, custom/classification models, containers, managed identities, or v4.0 migrations, and other Azure AI Document Intelligence related development tasks. Not for Azure AI Search (use azure-cognitive-search), Azure AI Vision (use azure-ai-vision), Azure AI Custom Vision (use azure-custom-vision), Azure AI Video Indexer (use azure-video-indexer).

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。

JTBD workflow classification and routing - ODI two-phase framework, five job types with workflow sequences, baseline type selection, workflow anti-patterns, and common recipes

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。

Strategic DDD — bounded context discovery, context mapping patterns, subdomain classification, ubiquitous language, and organizational alignment

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。

DIVIO/Diataxis four-quadrant documentation framework - type definitions, classification decision tree, and signal catalog

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。

Use when a brand faces a communications CRISIS or a campaign is failing in public — L1 to L5 severity classification, a first-four-hours process, response templates by type, an escalation matrix, a do-not-do list, holding statements, and a post-mortem. Trigger on 'PR crisis', 'crisis playbook', 'a complaint is going viral', 'bad reviews are spreading', 'our content caused backlash', 'we are getting attacked online'. Also use when the user forwards an angry thread and asks what to do right now. Not for — monitoring before anything blows up, see `15-social-listening-global`; diagnosing weak performance numbers, see `03-performance-eval-global`; the routine post-campaign review, see `63-campaign-retrospective-global`.

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。

Write or review manual Zephyr test cases with 1-condition-per-TC granularity, Module_Action on Screen when Condition naming, platform prefix rules, and High/Normal/Low priority classification. Use for test-case authoring and review; defer Jira traceability, linking, and pushing cases to Zephyr.

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。

Train object-detection, image-classification, or SAM segmentation models on Hugging Face Jobs. Use for vision fine-tuning and evaluation; use huggingface-llm-trainer for language models.

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。

Incident severity classification, runbook templates, root cause analysis, and post-incident 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。

KVKK and GDPR compliance patterns - consent management, right to erasure, breach notification, audit logging, cookie consent, and data classification.

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。

GDPR data handling, audit logging, data classification, retention policies, and consent management for regulatory compliance.

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。