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概要と使いどころ
Use when working with Tfsec — tfsec Terraform security scanning. Covers static analysis of Terraform code, custom rule creation, CI integration, severity filtering, module scanning, and remediation guidance. Use when scanning Terraform configurations for security issues, creating custom security rules, or integrating security checks into CI pipelines.
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。
Coordinate evidence based reconstruction from scans, photos, plans, and measurements into a reviewable Blender architectural model, with photographic appearance, renders and portable browser delivery when requested.
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。
Fit and independently validate rigid scan alignment from named, source traceable correspondences.
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。
Preserve and inventory scan archives while retaining capture variants, hashes, calibration, and frame provenance.
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 container images, filesystems, and Kubernetes manifests for vulnerabilities, misconfigurations, exposed secrets, and license compliance issues using Aqua Security Trivy with SBOM generation and CI/CD 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。
Scan container images for known vulnerabilities using Anchore Grype with SBOM-based matching and configurable severity thresholds.
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。
Trivy is a comprehensive open-source vulnerability scanner by Aqua Security that tespit etme (s) vulnerabilities in OS packages, language-specific dependencies, misconfigurations, secrets, and license violati
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。
bu skill covers implementing automated security scanning for Infrastructure as Code (IaC) templates using tools like Checkov, tfsec, and KICS. It addresses Tespit etme misconfigurations in Terraform, CloudFormation, Kubernetes manifests, and Helm charts before Dağıt:ment, establishing policy-based governance, and integrating IaC scanning into CI/CD pipelines to prevent insecure cloud resource provisioning.
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。
Perform security risk analysis on Kubernetes resource manifests using Kubesec to identify misconfigurations, privilege escalation risks, and deviations from security 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。
Securing container registry images by implementing vulnerability scanning with Trivy and Grype, enforcing image signing with Cosign and Sigstore, configuring registry access controls, and building CI/CD pipelines that prevent Dağıt:ing unscanned or unsigned images.
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。
Configures Fail2ban with custom filters and actions to detect port scanning activity, SSH brute force attempts, and network reconnaissance, automatically banning offending IP addresses and alerting security teams to suspicious network probing.
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。
URLScan.io is a free service for scanning and analyzing suspicious URLs. It captures screenshots, DOM content, HTTP transactions, JavaScript behavior, and network connections of web pages in an isolat
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 agent skills for security issues. Use when asked to "scan a skill", "audit a skill", "review skill security", "check skill for injection", "validate SKILL.md", or assess whether an agent skill is safe to install. Checks for prompt injection, malicious scripts, excessive permissions, secret exposure, and supply chain risks.
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。
Audit and improve website readiness for AI agents using the Cloudflare "Is It Agent Ready?" scanner (isitagentready.com). Covers scanning via API, interpreting results, generating implementation prompts, and fixing every check. Use when the user mentions "agent ready", "isitagentready", "AI agent scan", "agent readiness", "agent-ready score", "MCP server card", "agent skills index", "markdown for agents", "content signals", "web bot auth", "agent discovery", "RFC 9727", "RFC 8288", "RFC 9728", "SEP-1649", "WebMCP", "x402", "UCP", "ACP", or wants to make a website discoverable and usable by AI agents.
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。
This skill enables Claude to perform comprehensive accessibility audits. It uses the accessibility-test-scanner plugin to identify WCAG 2.1/2.2 compliance issues, validate ARIA attributes, check keyboard navigation, and assess screen reader compatibility. Use this skill when the user requests an accessibility scan, audit, or compliance check, or when terms like "WCAG", "ARIA", "screen reader", "accessibility testing", or "a11y" are mentioned. It provides actionable insights for improving web application accessibility.
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。
Assigns GO terms, Pfam/InterPro domains, KEGG orthologs, EC numbers, and product names to predicted proteins using eggNOG-mapper (orthology), InterProScan (domain signatures), and KofamScan (KEGG), routing specialized functions to dbCAN/antiSMASH/AMRFinderPlus/SignalP. Covers the orthology-vs-domain-vs-homology paradigms, the annotation-error percolation cascade, domain-presence-is-not-function, GO IEA circularity in enrichment, evidence tiering, and bit-score/coverage thresholds. Use when adding functional annotation to predicted genes, choosing between eggNOG-mapper and InterProScan, or judging how much to trust a functional label.
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。
Runs cis-pQTL Mendelian randomization for drug-target validation using UKB-PPP (Olink), deCODE (SomaScan), Fenland, INTERVAL, ARIC, and FinnGen-PPP proteomes plus colocalization triangulation, phenome-wide on-target adverse-effect scans, cross-platform Olink/SomaScan replication, and PAV (protein-altering variant) sensitivity. Use when nominating or de-risking a drug target from plasma-proteome GWAS, mimicking pharmacological inhibition via cis-pQTL instruments, separating shared-causal from LD-confounded signal under the Schmidt 2020 cis-MR framework, screening on-target adverse phenotypes pheWAS-style, or producing publication-grade STROBE-MR plus PP.H4 evidence for a target gene.
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。
ステージング環境にデプロイ済みのサーバーに対してランタイム検証を実行する。HTTPヘッダー・動的プローブ・認証テストに特化。手動呼び出し専用: /sec-runtime-scan [環境名]
リリース前の全ファイル静的解析スキル。プロジェクト構造を自動検出し、ソースモジュールごとのサブエージェントと依存関係スキャンを並列実行してコードベース全体の脆弱性を検出する。手動呼び出し専用: /sec-full-scan
Chief Security Officer mode. Infrastructure-first security audit: secrets archaeology, dependency supply chain, CI/CD pipeline security, LLM/AI security, skill supply chain scanning, plus OWASP Top 10, STRIDE threat modeling, and active verification. Two modes: daily (zero-noise, 8/10 confidence gate) and comprehensive (monthly deep scan, 2/10 bar). Trend tracking across audit runs. Use when: "security audit", "threat model", "pentest review", "OWASP", "CSO review". (gstack) Voice triggers (speech-to-text aliases): "see-so", "see so", "security review", "security check", "vulnerability scan", "run security".
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。
Content sanitization and hidden-content detection for agent skill security. Scans markdown, HTML, and text for visually hidden but agent-readable attacks: CSS-hidden text (display:none, color:white, font-size:0, opacity:0), HTML comments with instructions, collapsible details sections, zero-width unicode, homoglyphs, misleading links, and inline HTML in markdown. Enforces mandatory sanitization before external content enters agent context. Load as part of the secure-* sequence during any repo scan or skill audit. Also load for sanitize content, check hidden text, scan markdown attacks, strip HTML, detect invisible instructions, check zero-width chars. Core principle: visibility does not equal influence — hidden content is more dangerous than visible content because agents process it but humans cannot see it.
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。
Security audit orchestrator for agent skills — scans for prompt injection, data exfiltration, credential theft, supply chain risks, and instruction hierarchy violations before any skill is installed, created, improved, or read from a GitHub repo. Load when creating skills from external sources, when improve-skills reads from GitHub repos, when research-skill fetches community SKILL.md files, when a user installs a third-party skill, or when the user asks to audit skill security, scan for injection, check if a skill is safe, scan all skills, or run a security sweep. Orchestrates all secure-* skills in sequence. Content is SAFE only if ALL secure-* skills return SAFE. 36% of community skills contain flaws (Snyk ToxicSkills 2026). This skill is the first line of defense.
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。
Security checks for repository ingestion — scans repos for poisoned examples, dependency and supply-chain attacks, file/path traversal, format-based attacks, and enforces quarantine-before-commit. Load as part of the secure-* skill sequence whenever an agent reads, ingests, or learns from a GitHub repository. Also load when the user asks to check a repo for poisoned code, scan dependencies, verify supply chain safety, check for path traversal, scan repo files for attacks, or audit a repo before ingestion. Covers Issues 3, 4, 7, 8 from the agent security threat model: poisoned training data, dependency attacks, file/path attacks, and format-based attacks.
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。
Assigns GO terms, Pfam/InterPro domains, KEGG orthologs, EC numbers, and product names to predicted proteins using eggNOG-mapper (orthology), InterProScan (domain signatures), and KofamScan (KEGG), routing specialized functions to dbCAN/antiSMASH/AMRFinderPlus/SignalP. Covers the orthology-vs-domain-vs-homology paradigms, the annotation-error percolation cascade, domain-presence-is-not-function, GO IEA circularity in enrichment, evidence tiering, and bit-score/coverage thresholds. Use when adding functional annotation to predicted genes, choosing between eggNOG-mapper and InterProScan, or judging how much to trust a functional label.
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。