「requirements」の検索結果

Guides privacy audit evidence collection processes including evidence planning, sampling strategies, documentation standards, chain of custody, interview techniques, system walkthrough procedures, and evidence evaluation. Covers ISO 19011 evidence categories (records, statements of fact, observations) and ISACA audit evidence requirements for privacy compliance assessments. Keywords: audit evidence, evidence collection, sampling, chain of custody, audit documentation, interview techniques.

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。

Implements GDPR Art. 22 automated decision-making and AI Act Art. 14 human oversight requirements for AI systems. Covers identification of solely automated decisions, meaningful human intervention design, logic explanation mechanisms, and contestation procedures. Keywords: Art. 22, automated decision, human oversight, AI Act, profiling, contestation.

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。

Guides audit follow-up and verification processes including follow-up scheduling, remediation effectiveness testing, finding closure criteria, re-testing procedures, status reporting, and escalation of unremediated findings. Implements IIA Standard 2500 monitoring requirements and ISO 19011 follow-up guidance for privacy audit engagements. Keywords: audit follow-up, verification testing, finding closure, remediation effectiveness, re-testing, follow-up audit.

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。

Preparing EU AI Act compliance documentation for high-risk AI systems. Covers Annex III classification, technical documentation under Art. 11, conformity assessment, risk management systems, and CE marking requirements. Keywords: EU AI Act, high-risk AI, Annex III, conformity assessment, CE marking.

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。

Manages GDPR Article 22 rights related to solely automated decision-making and profiling, including identification of automated decisions, meaningful human oversight implementation, logic explanation requirements, and contestation mechanisms. Activate for automated decision, profiling, Art. 22, algorithmic decision, AI decision queries.

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。

Implements 42 CFR Part 2 protections for substance use disorder patient records. Covers written consent requirements stricter than HIPAA, re-disclosure prohibition, court order procedures, qualified service organization agreements, and 2024 amendments aligning Part 2 with HIPAA. Keywords: 42 CFR Part 2, substance use disorder, SUD records, re-disclosure, consent, Part 2 amendments.

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。

Implements age-gating mechanisms for online services to restrict access based on user age. Covers hard gates versus soft gates, neutral age prompts, re-verification triggers, circumvention prevention, and regulatory requirements under GDPR, COPPA, UK Online Safety Act, and DSA. Keywords: age gate, age restriction, neutral prompt, children, online services, access control.

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。

Implement centralized audit logging and SIEM integration. Configure log retention and security monitoring. Use when implementing audit trail requirements.

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。

Architectural decision-making framework. Requirements analysis, trade-off evaluation, ADR documentation. Use when making architecture decisions or analyzing 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。

Clarify requirements before implementing. Use when serious doubts arise.

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 meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks.

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 the user needs product management workflows such as RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, go-to-market strategy, feature prioritization, research synthesis, or requirements documentation.

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。

PRD writing and product definition expert. Use when writing PRDs, user stories, acceptance criteria, or prioritizing features. Covers RICE/MoSCoW frameworks, agile requirements, and specification best practices.

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。

On-page SEO optimization techniques including keyword density, meta tags, heading structure, and readability. Use when optimizing existing content or validating new content against SEO requirements.

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。

Full Ads Funnel Architect. Builds a complete advertising funnel across TOFU, MOFU, BOFU, and Retargeting stages with platform-specific templates, audience targeting, ad formats, copy angles, landing page requirements, KPIs, and budget allocation for Meta, Google, and LinkedIn.

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/B Testing Plan Generator. Creates structured testing roadmaps with prioritized test sequences, duration calculators, sample size requirements, statistical significance thresholds, hypothesis templates, and 90-day testing calendars for Meta, Google, and LinkedIn.

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。

Fix "blocked: event rejected by relay policy" errors when publishing Kind 34236 (video) events to divine relays. Use when: (1) Kind 0 profile events succeed but Kind 34236 fails, (2) Generic policy rejection with no specific reason, (3) Video events work on other relays but fail on divine relays. The divine relay requires thumbnails for all video events - stricter than NIP-71 spec.

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。

Analyzes test suites and suggests optimal test execution order based on code change impact and project requirements. Use when optimizing CI/CD pipelines, deciding which tests to run before committing, or selecting critical tests under time constraints. Prioritizes tests by analyzing recently modified files, test dependencies, and coverage overlap. Outputs detailed rankings with priority scores and reasoning to help teams run the most impactful tests first.

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。

Interview-based strategic planning for complex software tasks. Conducts structured requirements gathering, gap analysis, and generates detailed work plans before implementation begins.

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。

Generate formal specifications including preconditions, postconditions, invariants, and contracts from code or requirements. Use this skill when documenting APIs, creating formal verification annotations, defining function contracts, specifying class invariants, writing design-by-contract code, or preparing code for formal verification. Supports multiple specification languages including JML, ACSL, Dafny, Eiffel contracts, and documentation annotations.

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。

Scan repositories for newly disclosed CVEs in dependencies after a specific cutoff date. Takes a repository path, cutoff date (YYYY-MM-DD), and optional parameters for transitive dependencies. Parses dependency manifests (package.json, pom.xml, requirements.txt, go.mod, Cargo.toml) and lockfiles to extract exact versions. Queries vulnerability databases (OSV.dev, NVD, GitHub Advisory) to identify CVEs disclosed strictly after the cutoff date. Distinguishes between newly disclosed CVEs and previously known CVEs. Use when: (1) Performing security audits to find new vulnerabilities since last review, (2) Checking if new CVEs affect a historical codebase version, (3) Generating compliance reports showing vulnerability status at specific dates, (4) Tracking security posture changes over time. Supports npm, Maven, pip, Go modules, Cargo, and other major ecosystems.

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。

Generate implementation code and tests from written specifications. Use when the user provides specifications (natural language descriptions, formal specs, requirements documents, API specs) and asks Claude to implement the described functionality. Supports data structures, algorithms, classes, functions, and includes automatic test generation to validate implementation against specification.

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。

Compares old and new requirement documents, analyzes code repository impact, and generates detailed modification plans. Use when Claude needs to: (1) Compare requirement versions and identify changes, (2) Map requirement changes to code components, (3) Identify components to modify, delete, or add, (4) Analyze dependencies and integration points, (5) Assess test impact, (6) Generate comprehensive modification plans in Markdown format. Supports text/Markdown requirements and analyzes feature-level, functional, and API changes.

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。

Quickly analyzes Python repositories to understand their purpose, structure, and setup requirements. Use when Claude needs to onboard to a new Python codebase, understand project structure, identify entry points, determine dependencies, or generate setup instructions. Trigger when users ask to "analyze this Python repo", "understand this codebase", "how do I run this project", "what does this repo do", or provide a Python repository path for quick start guidance.

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。