「ssm」の検索結果

Helps a teacher prepare to teach an existing K-12 lesson (math / ELA / science / social studies) — a prep partner that thinks through the lesson's key student task with the teacher and leaves a short teacher-only prep note. Triggers on asks to internalize, prepare for, get ready to teach, or understand a lesson, including implicit ones ("help me get ready for tomorrow's lesson"), and right after another skill built a lesson, which it can follow. Not for building or adapting a lesson, grading, rubrics, assessment feedback, or generating quizzes or student-facing material, and not for single-fact lookups a sentence would answer ("what standard is this?", "how long is this lesson?").

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Adapts an existing K-12 lesson (math, ELA, science, or social studies) for students at different proficiency levels (below / at / above grade level). Load this skill BEFORE asking the teacher any clarifying question about the lesson, tiers, or student levels. Triggers on explicit asks to differentiate, tier, or scaffold a lesson, and on implicit signals like "my students are at different levels". Produces 1 teacher-facing differentiation plan + 3 student-ready tier documents as editable, printable documents in a single output turn (shared content is written once, so tiers cannot drift). Uses the Learning Commons Knowledge Graph when connected; works without it. This skill adapts a lesson the teacher brings or names. Not for creating a new lesson from scratch — a new-lesson request that asks for differentiated or leveled materials is k12-lesson-plan-creation's job, one package. Not for grading, rubrics, assessment feedback, or quizzes.

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。

Code comment accuracy verification, documentation completeness assessment, comment rot detection.

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。

Product Requirements Document writing - PRD templates, MoSCoW prioritization, user personas, competitive analysis, feature specs, acceptance criteria, 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。

Audits existing tests in any language using formal, research-backed test smell names and the testsmells.org 19-smell academic taxonomy. Use when the caller asks for an academic or citable test-smell review, named smell categories, or a formal severity-ranked smell assessment. Covers Assertion Roulette, Conditional Test Logic, Mystery Guest, Eager Test, Sleepy Test, Unknown Test, Sensitive Equality, and the rest of the catalog across .NET, Python, JavaScript/TypeScript, Java, Go, Ruby, Rust, Swift, Kotlin, PowerShell, and C++. DO NOT USE FOR a quick pragmatic test review (use test-anti-patterns), writing or running tests, framework migration, coverage, or assertion-diversity metrics.

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Comprehensive data quality assessment against business rules, schema constraints, and freshness expectations. Activate when validating data pipeline outputs before production use, auditing a dataset against defined business rules, or producing a quality scorecard for a data 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。

Android and iOS application security testing — static and dynamic analysis, APK/IPA inspection, OWASP MASVS/MASTG verification, secure-storage and transport review, and mobile malware triage for authorized assessments

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。

Passive and active reconnaissance, subdomain enumeration, DNS analysis, technology fingerprinting, and OSINT data correlation for authorized security assessments

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。

SSL/TLS auditing, cipher suite analysis, hash algorithm identification, encryption implementation review, and cryptographic weakness detection in code

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。

Operational Technology and industrial control system security — Purdue model segmentation, industrial protocol analysis (Modbus, DNP3, S7, EtherNet/IP), PLC/HMI exposure, IEC 62443 alignment, and MITRE ATT&CK for ICS, for authorized and safety-conscious assessments

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。

AWS/Azure/GCP security auditing, container and Kubernetes hardening, Infrastructure as Code scanning, and cloud compliance assessment

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Governance, risk, and compliance — risk assessment and scoring, control mapping across NIST CSF 2.0 / ISO 27001:2022 / SOC 2 / CIS Controls v8, gap analysis, audit evidence preparation, and security policy generation

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LLM and AI application security testing — prompt injection, jailbreak resistance, OWASP LLM Top 10 (2025), RAG and agent/tool-use security, model supply chain, and AI red teaming for authorized assessments

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。

Responsible AI development and ethical considerations. Use when evaluating AI bias, implementing fairness measures, conducting ethical assessments, or ensuring AI systems align with human values.

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Map your security posture against the NIST Cybersecurity Framework 2.0 (Govern, Identify, Protect, Detect, Respond, Recover). Produce a gap analysis, current/target tier assessment, and roadmap in the governance language that boards, auditors, and CISOs actually use. Use when the user mentions 'NIST CSF,' 'CSF 2.0,' 'cybersecurity framework,' 'security posture,' 'governance mapping,' 'CSF gap analysis,' 'CSF tiers,' 'cybersecurity maturity,' 'security roadmap,' 'CISO report,' 'board reporting,' 'security program,' or needs to translate technical findings into governance language.

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Gather and correlate open source intelligence from public sources for authorized investigations, threat intelligence, and attack surface assessment. Use when the user mentions 'OSINT,' 'open source intelligence,' 'digital footprint,' 'public records,' 'threat intelligence,' 'investigate a domain,' or needs to research a target using publicly available data.

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Implement and audit privacy controls in product and infrastructure — GDPR, CCPA / CPRA, LGPD, PIPEDA. Covers data minimization, lawful basis, consent management, data subject access requests (DSARs — access, deletion, portability), data processing agreements, DPIA / TIA, breach notification timing, data classification, and the technical implementation of 'right to be forgotten' across backups, caches, analytics, and third parties. Use when the user mentions 'GDPR,' 'CCPA,' 'CPRA,' 'data privacy,' 'privacy engineering,' 'data subject access request,' 'DSAR,' 'right to deletion,' 'right to be forgotten,' 'data portability,' 'consent management,' 'cookie consent,' 'data minimization,' 'DPIA,' 'data protection impact assessment,' 'breach notification,' 'BAA,' 'DPA,' 'data processing agreement,' 'sub-processor,' 'cross-border data transfer,' 'SCCs,' or needs to implement or review privacy controls.

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。

DEX liquidity depth assessment, slippage estimation, and pool composition analysis for Solana tokens

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。

MEV exposure assessment, sandwich attack detection, and protection strategies for Solana DEX trading

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。

Apply a UX lens to a user-facing change: whether it serves the user's real goal and whether the path through it holds together, using the Understanding, Bridging, and Flowing contexts. Use when scoping, planning, or assessing any change that affects what a user sees or does. Loaded as a lens during planning and 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。

Comprehensive biosignal processing toolkit for analyzing physiological data including ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use this skill when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements. Applicable for heart rate variability analysis, event-related potentials, complexity measures, autonomic nervous system assessment, psychophysiology research, and multi-modal physiological signal integration.

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 detailed implementation plans for complex tasks. Creates comprehensive strategic plans in Markdown format with objectives, step-by-step implementation tasks using checkbox format, verification criteria, risk assessments, and alternative approaches. All plans MUST be validated using the included validation script. Use when users need thorough analysis and structured planning before implementation, when breaking down complex features into actionable steps, or when they explicitly ask for a plan, roadmap, or strategy. Strictly planning-focused with no code modifications.

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。

Pre-implementation confidence assessment (≥90% required). Use before starting any implementation to verify readiness with duplicate check, architecture compliance, official docs verification, OSS references, and root cause identification.

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。

Enterprise-grade compliance architecture for SOC 2, HIPAA, GDPR, PCI-DSS. Provides compliance checklists, security controls, audit guidance, and regulatory requirements for serverless and cloud architectures. Activates for compliance, HIPAA, SOC2, SOC 2, GDPR, PCI-DSS, PCI DSS, regulatory, healthcare data, payment card, data protection, audit, security standards, regulated industry, BAA, business associate agreement, DPIA, data protection impact 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。