2.4万 件 ・ 関連度順
概要と使いどころ
AI-powered skill recommendation engine for dotnet-agent-harness. Analyzes project context and recommends relevant skills based on detected frameworks, packages, and patterns. Triggers on: recommend skill, suggest skills, what skill should I use, skill suggestion, project analysis recommendation.
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。
Base implementation skill for this repository across .NET/C#, backend APIs, database/ORM, frontend Vue/Quasar, and Rust with Clean Architecture rules. Use when the user asks to build features, fix bugs, refactor modules, or improve code-level performance, and use specialized skills as inheritance layers when available.
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。
Base implementation skill. Use for code changes, bug fixes, refactors, and script work across .NET/C#, backend APIs, database/ORM, Vue/Quasar frontend, Rust, PowerShell, Docker, K8s, CI/CD, security, observability, and SRE domains. Specialized skills extend this as a base.
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。
Design, implement, and stabilize automated tests (unit, integration, E2E) for .NET/C#, Rust, APIs, and frontend flows. Use when the user asks to create tests, increase coverage, fix flaky tests, or validate behavior changes.
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。
Create or update active planning documents under `planning/active`, then define the execution slices, validations, specialist handoff, and closeout expectations. Use when the task is non-trivial, multi-step, or explicitly asks for planning.
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。
Design, implement, and stabilize automated tests in this repository (unit, integration, and E2E) for .NET/C#, Rust, APIs, and frontend flows. Use when the user asks to create tests, increase coverage, fix flaky tests, or validate behavior changes.
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 wiring shadcn/ui primitives, forms or admin UI in site-os — the component mechanics, the VBField validation layer, and the UI bugs that have actually shipped here. For brand identity (colour, type, logo, voice) load brand instead; that skill wins on any disagreement.
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 auditing or improving example.com's SEO/indexing — Google Search Console issues (404s, sitemap, "discovered not indexed"), on-page checks (title/meta/canonical/OG/H1/internal links), or wiring search-engine notification (IndexNow/GSC/Bing/Yandex). Also use when the operator pastes GSC findings and asks to fix + validate.
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 standing up a fresh deployment of this codebase (or the public vigyan-site-os template) — populates company identity, branding and starting content without committing any of it, and decides for each value whether it belongs in platform env, encrypted DB secrets, DB config, or an admin screen.
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。
Validate built features through conversational UAT
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。
Automatically advance to the next logical step in the GSD 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。
Show available GSD commands and usage guide
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 AI design contract (AI-SPEC.md) for phases that involve building AI systems — framework selection, implementation guidance from official docs, and evaluation strategy
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 suspicious PowerShell execution patterns including encoded commands, download cradles, AMSI bypass attempts, and constrained language mode evasion.
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 typosquatting attacks in npm and PyPI package registries by analyzing package name similarity using Levenshtein distance and other string metrics, examining publish date heuristics to identify recently created packages mimicking established ones, and flagging download count anomalies where suspicious packages have disproportionately low usage compared to their legitimate targets. The analyst queries the PyPI JSON API and npm registry API to gather package metadata for automated comparison. Activates for requests involving package typosquatting detection, dependency confusion analysis, malicious package identification, or software supply chain threat hunting in package registries.
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。
Analyzes and simulates BGP hijacking scenarios in authorized lab environments to assess route origin validation, RPKI deployment, and BGP monitoring defenses against prefix hijacking and route leak attacks on internet routing infrastructure.
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 process injection techniques (T1055) including classic DLL injection, process hollowing, and APC injection by analyzing Sysmon events for cross-process memory operations, remote thread creation, and anomalous DLL loading 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。
Exploits JWT algorithm confusion vulnerabilities where the server's token verification library accepts the algorithm specified in the JWT header rather than enforcing a fixed algorithm. The tester manipulates the alg header to switch from RS256 to HS256 (using the RSA public key as the HMAC secret), sets alg to none to bypass signature verification, or exploits kid/jku/x5u header injection to supply attacker-controlled keys. Activates for requests involving JWT algorithm confusion, alg none attack, key confusion attack, or JWT signature bypass.
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。
Tests APIs for excessive data exposure where endpoints return more data than the client application needs, relying on the frontend to filter sensitive fields. The tester intercepts API responses and analyzes them for leaked PII, internal identifiers, debug information, or sensitive business data that the UI does not display but the API transmits. This maps to OWASP API3:2023 Broken Object Property Level Authorization. Activates for requests involving API data leakage testing, excessive data exposure, response filtering bypass, or API over-fetching.
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。
Systematically remove malware, backdoors, and attacker persistence mechanisms from infected systems while ensuring complete eradication and preventing re-infection.
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。
Executes authorized phishing simulation campaigns to assess an organization's susceptibility to email-based social engineering attacks. The tester designs realistic phishing scenarios, builds credential harvesting infrastructure, sends targeted phishing emails, and tracks open rates, click-through rates, and credential submission rates to measure human security awareness. Activates for requests involving phishing simulation, social engineering assessment, email security testing, or security awareness measurement.
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。
Identifies and exploits insecure local data storage vulnerabilities in Android and iOS mobile applications including unencrypted databases, world-readable files, insecure SharedPreferences, plaintext credential storage, and improper keychain/keystore usage. Use when performing mobile penetration testing focused on OWASP M9 (Insecure Data Storage) or assessing compliance with MASVS-STORAGE requirements. Activates for requests involving mobile data storage security, local storage exploitation, SharedPreferences analysis, or mobile data leakage 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。
Executes authorized attack simulations against Active Directory environments to identify misconfigurations, weak credentials, dangerous privilege paths, and exploitable trust relationships that could lead to domain compromise. The tester uses BloodHound for attack path analysis, Mimikatz for credential extraction, and Impacket for protocol-level attacks including Kerberoasting, AS-REP Roasting, and delegation abuse. Activates for requests involving Active Directory pentest, AD attack simulation, domain compromise testing, or Kerberos attack 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。
Identifying and exploiting insecure deserialization vulnerabilities in Java, PHP, Python, and .NET applications to achieve remote code execution during authorized penetration tests.
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。