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概要と使いどころ
Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems.
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Advogado especialista em todas as areas do Direito brasileiro: familia, criminal, trabalhista, tributario, consumidor, imobiliario, empresarial, civil e constitucional.
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Estratega de Inteligencia de Dominio de Andru.ia. Analiza el nicho específico de un proyecto para inyectar conocimientos, regulaciones y estándares únicos del sector. Actívalo tras definir el nicho.
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Advogado criminalista especializado em Maria da Penha, violencia domestica, feminicidio, direito penal brasileiro, medidas protetivas, inquerito policial e acao penal.
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tespit etmeunauthorized SaaS and cloud service usage (shadow IT) by analyzing proxy logs, DNS query logs, and netflow data using Python pandas for traffic pattern analysis and domain classification.
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。
OSINT kategorisi SKILL.md — Kullanıcı araştırması, sosyal medya, subdomain keşfi araçları kurma rehberi
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Crypto kategori SKILL.md — RSA, ECC, AES, hash, encoding saldırıları için gerekli araçları kurma rehberi
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 building creative browser demos with @chenglou/pretext — DOM-free text layout for ASCII art, typographic flow around obstacles, text-as-geometry games, kinetic typography, and text-powered generative art. Produces single-file HTML demos by default.
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 for the infrastructure design phase between domain exploration and Lean formalization — deriving non-functional requirements from the Lean model, deciding environments (test/local/prod), identity provider, the relational database's product, version and configuration (the storage kind is fixed to relational), ID representation, and the list of things NOT to build. Produces documents/infra-design with INFRA-D/A/Q entries.
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 to create, update or verify the Lean 4 executable specification under lean/ from the exploration documents (event-timeline, hotspots, ubiquitous-language, ux-review, model-review) — initial generation, reflecting a session's results, fixing lake build, adding a command or a screen, checking a proposed feature against the model. Formalization questions go to model-review.md as MQ, never to the expert directly.
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 whenever the screens, UX, wording, feedback after actions, accessibility, or layout of frontend/ come up, even without the word "review" — delegates to the frontend-ux-reviewer agent, which runs the dev screens against the Lean CLI with Playwright and reports with evidence. Not for reviewing the domain model itself (that is the ddd skill's 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。
Use to start a new product on Cradle or to add the Cradle skeleton to an existing repository — writes cradle.json, the project-facts instruction (.apm/instructions/project.instructions.md), documents/{ddd,ai-notes,infra-design,codebase} templates, CI, and a compiling Lean executable-spec scaffold with a minimal example domain, mockup and CLI.
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 for the frontend phase after the API contract exists — deciding the screens as units of work (one job a person finishes in one go, per actor of the event timeline), collecting the views and commands each screen needs, keeping the screen map in frontend/README.md, building against the Lean CLI, then handing over to frontend-ux-review and the human screen check. Not for the spec-animation mockup (domain-mockup).
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。
Detect DNS-based data exfiltration by analyzing Zeek dns.log for high-entropy subdomains and anomalous query patterns
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。
Detect NTLM relay attacks through Windows Security Event correlation by analyzing Event 4624 LogonType 3 for IP-to-hostname mismatches, identifying Responder/LLMNR poisoning artifacts, auditing SMB and LDAP signing enforcement across the domain, and detecting NTLM downgrade attacks from NTLMv2 to NTLMv1 using event log analysis.
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。
Detect unauthorized SaaS and cloud service usage (shadow IT) by analyzing proxy logs, DNS query logs, and netflow data using Python pandas for traffic pattern analysis and domain classification.
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。
Detect Golden Ticket attacks in Active Directory by analyzing Kerberos TGT anomalies including mismatched encryption types, impossible ticket lifetimes, non-existent accounts, and forged PAC signatures in domain controller event logs.
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Detect data exfiltration through DNS tunneling by analyzing query entropy, subdomain length, query volume, TXT record abuse, and response payload sizes using passive DNS monitoring.
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Detect DCSync attacks where adversaries abuse Active Directory replication privileges to extract password hashes by monitoring for non-domain-controller accounts requesting directory replication via DsGetNCChanges.
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Conduct internal Active Directory reconnaissance using BloodHound Community Edition to map attack paths, identify privilege escalation chains, and discover misconfigurations in domain environments.
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Build an automated system to track adversary infrastructure using passive DNS, certificate transparency, WHOIS data, and IP enrichment to map and monitor threat actor command-and-control networks.
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Build an automated pipeline to defang indicators of compromise (URLs, IPs, domains, emails) for safe sharing and distribute them in STIX format through TAXII feeds and threat intelligence platforms.
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Analyzes Windows Security, System, and Sysmon event logs in Splunk to detect authentication attacks, privilege escalation, persistence mechanisms, and lateral movement using SPL queries mapped to MITRE ATT&CK techniques. Use when SOC analysts need to investigate Windows-based threats, build detection queries, or perform forensic timeline analysis of Windows endpoints and domain controllers.
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Establish SAML 2.0 identity federation between on-premises Active Directory and Azure AD (Microsoft Entra ID) for seamless cross-domain authentication and SSO to cloud applications.
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。