Typosquatting detection, install script analysis, dependency confusion prevention, and phantom dependency detection for npm/pip.
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概要と使いどころ
Typosquatting detection, install script analysis, dependency confusion prevention, and phantom dependency detection for npm/pip.
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。
Constructs secure, efficient CI/CD pipelines with supply chain security (SLSA), monorepo optimization, caching strategies, and parallelization patterns for GitHub Actions, GitLab CI, and Argo Workflows. Use when setting up automated testing, building, or deployment workflows.
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Build forms, validate data, and react to user input in Blazor. USE FOR adding forms, search boxes, filter panels, inline editing, data-entry UI, file uploads, validation (annotations or custom), handling form submissions, and binding input controls. Covers EditForm, built-in input components, DataAnnotationsValidator, custom validation, SSR form patterns (SupplyParameterFromForm, FormName, AntiforgeryToken, Enhance), and @bind for simple interactive controls. DO NOT USE for project scaffolding (see create-blazor-project) or prerendering issues (see support-prerendering).
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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
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Use when reviewing, designing, or modifying Java enterprise systems from a maintainer-authored or maintainer-sanitized NIS2 engineering evidence inventory. Supports essential or important entities, critical-sector services, managed service providers, supply-chain dependencies, and cybersecurity incident escalation obligations without ingesting raw code, logs, runbooks, tickets, provider documents, or other operational free text. Part of Plinth Toolkit
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Security: review git changes for vulnerabilities, threat-model a system's attack surface, audit supply-chain risks.
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Audit project dependencies, frameworks, languages, and dev tools for known vulnerabilities, CVEs, and security anti-patterns. Use when the user mentions 'dependency audit,' 'npm audit,' 'CVE,' 'vulnerable packages,' 'supply chain security,' 'outdated dependencies,' 'known vulnerabilities,' 'security advisory,' 'package security,' 'framework vulnerability,' 'is this package safe,' or needs to check whether their stack has known security issues.
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。
Token holder distribution, concentration metrics, insider detection, and supply 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。
Token supply dynamics, vesting analysis, inflation modeling, and valuation frameworks for crypto 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。
Use when attacking an AI/ML system or model — prompt injection & jailbreaks (Crescendo, Skeleton Key, Best-of-N), RAG/vector poisoning, agentic/MCP exploitation (CVE-2025-54136), ML supply-chain RCE (pickle CVE-2025-32434), model extraction / membership inference / adversarial suffixes (GCG)
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 gaining initial access to a target — phishing, payload delivery, HTML smuggling, ISO/IMG/MOTW bypass, supply-chain, credential stuffing, exposed-service exploitation
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Use when auditing source code for vulnerabilities — drive CodeQL/Semgrep/Joern to taint untrusted data source-to-sink across injection, memory safety, deserialization/prototype-pollution, secrets/crypto/authz/race, and supply-chain risks
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Plan an Instagram carousel slide by slide, up to 10 slides, with a hook slide that opens a loop, value slides that front-load the payoff, and a payoff slide that earns the save and follow. Picks a 2026 carousel formula (listicle, before/after, myth-buster, framework) by goal (saves, shares, follows), drafts each slide's text plus the caption, then publishes the images you supply via Publora. Use to structure a multi-slide carousel. Not for single-image captions (use ig-caption-writer).
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。
Draft an Instagram caption with the hook in the first 125 characters, a skimmable body, and one clear CTA, using a 2026 hook formula chosen by goal (saves, shares, comments, follows). Runs the humanizer pass and, on approval, publishes with the image or video you supply via the Publora media flow. Use to caption a single image or a Reel. Not for slide-by-slide carousels (use ig-carousel-planner) or auditing a draft (use ig-humanizer --mode audit).
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Applies NIST/CWE security hardening to Python and Rust code. Use when auditing code for vulnerabilities or proposing concrete security remediations.
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Verifies a package exists before install, defending against hallucination and slopsquatting. Use when adding, recommending, or installing a package.
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Use when a trained medical-imaging model needs its documentation. Fills a Model Card and a Datasheet for its dataset from facts you supply, adds a METRIC-informed data-quality pass and gates that no required section is empty. Never invents numbers, provenance or licence.
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Harden AI/LLM deployments against prompt injection, data exfiltration, model theft, and supply chain attacks.
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This skill should be used when the user asks to "create a location", "add a location", "magic system", "political system", "build the world", "add culture", "world history", "technology system", "religion", "economy", "map", "travel times", "routes", "calendar", "moons", "seasons", "naming language", "conlang names", "trade routes", "supply lines", "magic cost", "add a glossary term", "glossary", "invented word", or wants to develop any aspect of a story's world and setting. NOT for a glossary for translators (use adaptation).
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Threat-model product features, APIs, data flows, secrets, permissions, supply-chain changes, auth boundaries, and risky code paths before or during implementation. Use when touching authentication, authorization, payments, secrets, user data, uploads, webhooks, admin tools, innerHTML/eval/exec, dependency upgrades, or cross-tenant access.
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 project dependencies for known vulnerabilities, generate software bills of materials, and enforce license compliance across the software supply chain. Use when the user requests dependency scanning or provides relevant inputs for this workflow.
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Audit agent skills, plugins, prompts, manifests, scripts, dependencies, and bundled assets for provenance, prompt-injection, permission, execution, exfiltration, persistence, and update risk. Use when evaluating a third-party skill before installing, enabling, updating, publishing, or distributing it; reviewing an untrusted SKILL.md, agent configuration, MCP integration, archive, or repository; comparing a package with a known-good version; or investigating unexpected tool, network, credential, or filesystem behavior.
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Think and work like an expert Fire Protection Engineer. Use when a task calls for Fire Protection Engineer judgment. Reasons from NFPA 13 Hazen-Williams hydraulics (K-factor, remote area, hose stream) and NFPA 101 egress (occupant load, travel distance, capacity factors) through NFPA 92 smoke containment/management, ASET/RSET PBD, and FDS/CFAST/CONTAM/PyroSim modeling while treating breached compartmentation, C-factor/fitting errors, and supply-curve shortfall as first-class failure modes.
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Think and work like an expert Cardiologist. Use when a task calls for Cardiologist judgment. Reasons from oxygen supply-demand mismatch, forward flow, filling pressures, and pre-test probability through 12-lead ECG, TTE/TEE with ASE grading, cath hemodynamics, CMR, and ACC/AHA/ESC guidelines with risk scores like HEART, GRACE, and CHA2DS2-VASc, while treating context-free troponin elevation, low-flow low-gradient AS discordance, undiagnosed wide-complex tachycardia, and premature diagnostic closure as first-class failure modes.
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。