「sca」の検索結果

This skill should be used when the user asks to "write a poem", "write a limerick", "write a sonnet", "haiku", "villanelle", "ballad", "song lyrics", "a song for my character", "a rhyme", "rhyming couplets", "does this scan", "check the meter", "fix the rhythm of this poem", "rhyme scheme", "iambic pentameter", "a prophecy in verse", "a nursery rhyme", "rhyming picture book", or wants verse written, scanned, or revised, whether inside a story project or as a standalone poem. NOT for accidental rhymes in prose (use line-editing) or permissions for quoting someone else's poem or song lyrics (use editorial-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。

Photorealistic AAA art direction for Blender including photogrammetry cleanup, real-world scale, high-poly workflows, PBR accuracy, and scan optimization. Use for cinematic and AAA game realism.

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。

Detects PII in unstructured data including emails, documents, images, and logs using NER-based detection with spaCy and Microsoft Presidio, regex patterns, OCR integration, and confidence scoring. Keywords: PII detection, unstructured data, NER, spaCy, Presidio, OCR, regex, email scanning, document scanning.

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 the Art. 36 prior consultation process when a DPIA indicates high residual risk that cannot be mitigated. Covers required documentation per Art. 36(3), the 8-week DPA response timeline, outcome management, and interaction protocols with supervisory authorities. Keywords: prior consultation, Art. 36, supervisory authority, DPA, high residual risk, DPIA escalation, consultation 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。

Guides the end-to-end GDPR Data Protection Impact Assessment process under Article 35, including mandatory trigger identification per Art. 35(3), DPIA content requirements per Art. 35(7), and EDPB WP248rev.01 methodology. Activate for systematic profiling, large-scale special category processing, or large-scale public monitoring. Keywords: DPIA, Article 35, impact assessment, WP248, data protection, risk assessment.

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。

Implementation guide for GDPR Article 7(3) consent withdrawal mechanisms. Covers the equal ease requirement ensuring withdrawal is as easy as giving consent, one-click withdrawal implementation, cascading effects on downstream processing, third-party notification workflows, and technical architecture for real-time consent revocation.

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。

Comprehensive methodology for auditing website cookies and tracking technologies. Covers automated scanning, cookie categorization, lifecycle documentation, and compliance gap analysis referencing the Planet49 CJEU ruling (C-673/17).

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。

Scaffold complete Canvas LMS course structures from specs, templates, or existing courses. Creates modules, pages, assignments, and discussions in bulk. Use when asked to "build a course", "scaffold modules", "create course structure", "set up a new course", or "copy course structure".

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 or update repository-specific AGENTS.md instruction files from real repo evidence. Use when asked to create, design, scaffold, split, or improve root or scoped AGENTS.md files for Codex/Claude/agent workflows, especially when a repo needs directory-specific rules, validation commands, generated-file boundaries, or a short agent onboarding router.

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。

Applies the reasoning style of Ilya Sutskever (deep learning pioneer, co-founder of OpenAI and Safe Superintelligence Inc.) to problems involving AI architecture, scaling laws, alignment, and research strategy. Reach for this skill whenever discussing machine learning paradigms, the limits of compute and data, AGI timelines, superintelligence safety, or deciding between hardcoding vs. learning. Trigger this skill for questions about next-word prediction, reinforcement learning efficiency, generalization gaps, and transitioning from brute-force scaling to fundamental research, even if the user doesn't explicitly name him.

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。

Dead code removal via parallel scanning, reference verification, batch execution, and atomic commits. You are the ORCHESTRATOR — you scan, verify, batch, then delegate ALL removals.

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 prioritized CVE watchlists and actionable security recommendations for repositories. Use when analyzing CVE scan results, creating security reports, prioritizing vulnerability remediation, or generating security gate reports for CI/CD. Takes CVE scan results (JSON/SARIF from npm audit, pip-audit, Snyk), reachability analysis, and cutoff date as input. Combines severity, reachability, exploitability, and dependency criticality to rank CVEs by practical risk. Outputs markdown reports with concrete next-step guidance (immediate upgrade, monitor, ignore with justification, apply mitigation) suitable for issue trackers, security reviews, and CI security gates.

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。

Build, inspect, audit, and refactor Blender Geometry Nodes systems for procedural models, instancing, modular effects, curves, scattering, flocks, data visualization, fields, simulation zones, and node-graph cleanup. Use whenever a Blender task specifically calls for Geometry Nodes, reusable procedural node graphs, node connections/layout, or a scalable procedural asset.

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。

Framework for competitive landscape analysis across any industry. Use when creating competitor analysis, market positioning assessments, investment memos, strategic reviews, or any analysis requiring systematic evaluation of competitive dynamics. Triggers include requests for competitive landscape decks, peer comparisons, market structure analysis, strategic positioning assessments, and investment recommendations.

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。

WordPress performance code review and optimization analysis. Use when reviewing WordPress PHP code for performance issues, auditing themes/plugins for scalability, optimizing WP_Query, analyzing caching strategies, checking code before launch, or detecting anti-patterns, or when user mentions "performance review", "optimization audit", "slow WordPress", "slow queries", "high-traffic", "scale WordPress", "code review", "timeout", "500 error", "out of memory", or "site won't load". Detects anti-patterns in database queries, hooks, object caching, AJAX, and template loading.

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。

One-time autonomous design context discovery. Scans the codebase to extract design tokens, typography, colors, spacing, brand patterns, and tech stack, then writes a Design Context section to CLAUDE.md. Zero questions asked. Use when: 'setup design', 'design context', 'design tokens', 'brand discovery', 'design system scan', 'initialize design', 'teach 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。

Проводит структурированный сеанс дивергенции вокруг конкретной продуктовой проблемы или возможности. Встроены SCAMPER (7 ракурсов), 5 Whys для поиска корневой причины, кросс-доменное вдохновение, ограничивающие инновации, обратный брейншторм и матрица Impact/Effort для отбора. На выходе — ≥10 идей с детально проработанным Top-3. User-invoked only — do NOT auto-trigger. Triggers on /pm-brainstorm, "идеи для продукта", "продуктовый брейншторм", "дивергенция идей", "How Might We", "SCAMPER", "product brainstorm", "feature ideas".

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。

Automated security scanning for dependencies, code, containers with Trivy, Snyk, npm audit. Use for CI/CD security gates, pre-deployment audits, compliance requirements, or encountering CVE detection, outdated packages, license compliance, SBOM generation errors.

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。

Map the big picture around a topic or software repository by identifying its boundaries, layers, actors, components, relationships, flows, history, fault lines, and open questions, then explain how the pieces fit together and where to look next. Use when a user asks to understand a whole field, domain, technology, ecosystem, industry, codebase, architecture, unfamiliar repo, or phrases such as "give me the big picture", "map the landscape", "how does this all fit together?", "help me get oriented", or "what am I missing?"

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。

Vulnerability and security scan (defensive, your own repo): dependency CVEs plus risky code patterns (secrets, injection, weak authz), severity x reachability triaged and remediated without suppressing. Complements the built-in /security-review. Triggers on "absolute audit", "security audit", "are we vulnerable", "scan for CVEs", "check for secrets/injection", "harden this".

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, manage, and scale applications on Kubernetes clusters using manifests, Helm charts, and autoscaling configurations. Use when the user requests kubernetes deployment or provides relevant inputs for this workflow.

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。

Abusing Active Directory object ACLs (DACL/ownership) for privilege escalation and lateral movement (GenericAll, GenericWrite, WriteDACL, WriteOwner, AddMember, ForceChangePassword, and replication rights via DS-Replication-Get-Changes-All). Use when BloodHound CE shows an outbound control edge from a principal you own toward a higher-value object, and you want the exact bloodyAD/impacket command to weaponize that ACE, plus detection and remediation. DCSync is covered here strictly as a post-compromise technique, not a user entry path.

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。

Active Directory Certificate Services (AD CS) escalation techniques ESC1 through ESC17, driven by hand with Certipy (ly4k). Use when the target runs a Certificate Authority and you want to find vulnerable certificate templates or CA misconfigurations, request a certificate that impersonates a privileged user, and know the exact certipy command, what each ESC actually checks, the Windows Event IDs that fire, and the remediation. ESC1 and ESC8 are the two you hit most in the field.

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。