测试设计、漏洞检测、质量保证（1.3万 个）
The method for getting a cheaper model to match an agent's big-model answers by fixing instructions, inputs and setup. Use when asked to move an agent to a smaller or cheaper model, prove one model beats another, or compare models on an agent's test cases.
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Vite (フロントエンドビルドツール・開発サーバー, v8 / Rolldown) のリファレンス。 vite.config, defineConfig, server, build, optimizeDeps, HMR (import.meta.hot), import.meta.env, import.meta.glob, configureServer, transformIndexHtml, Environment API (DevEnvironment / ModuleRunner), SSR, library mode, JavaScript API, v7 から v8 移行。 テストは vitest スキル。
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Electron (Chromium + Node.js 製クロスプラットフォームデスクトップアプリフレームワーク, v44) の リファレンス。main / renderer / preload / utilityProcess, ipcMain / ipcRenderer / contextBridge, BrowserWindow / BaseWindow / WebContentsView / webContents, Electron Forge, autoUpdater, safeStorage, fuses, ASAR, contextIsolation / sandbox, code signing, MAS, crashReporter, contentTracing, debugging, E2E testing, breaking changes。
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Apple App Intents (Swift, Siri / Shortcuts / Apple Intelligence 連携フレームワーク) の リファレンス。AppIntent, AppEntity, AppEnum, EntityQuery, IntentParameter, AppShortcutsProvider, App Schemas (AppIntent マクロ), IndexedEntity (Spotlight), SnippetIntent, Visual Intelligence, IntentValueQuery, App Intents Testing, SiriKit (INIntent) 移行。
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Method for choosing and auditing an agent's reasoning_effort. Use when setting or reviewing reasoning_effort, when an agent was created with high, or when asked to cut reasoning spend. NOT for changing an agent's model (use test-model-selection).
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計画・差分レビュー・E2E計画・E2E結果を 1 つのブラウザページ（タブ切替）に統合表示する review-hub の操作手順。agent-review-kit のページを iframe で束ね、タブごとの承認ボタン（計画承認・E2E実行承認・PR作成承認）を ark のコメント（【承認】）として wait-comments で受け取る。ステータスバー（フェーズ進行・作業メモ）と中断ボタン、セッション再開手順（status / resume）も定義する。計画→実装→PR のように承認ゲートを挟むフロー系スキルから参照される。Use when a skill needs to show plans, diffs, or E2E results in one tabbed browser page, wait for a browser-side approval gate, or resume an interrupted review session.
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Picks the model a coding agent uses when a test or browser check sends an AI call. Use when choosing a model for any test, UI check, bench, or agent run, or when a test names Opus, Sonnet, Fable, Astra, or any model by habit.
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Improve test value and feedback cost when auditing slow, flaky, redundant or brittle tests; choosing tests during implementation; or reviewing test changes before a commit or PR. Keep ordinary implementation and pre-commit use scoped to the affected behavior, not a repository-wide audit.
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Disciplined diagnosis workflow for hard, intermittent, or multi-component bugs and performance regressions: inspect logs and existing evidence, build a feedback loop, test falsifiable hypotheses, instrument gaps, and verify the outcome. Use when the root cause is unclear, reproduction is unreliable, several causes or components are plausible, or performance has regressed. Do NOT use for obvious single-cause errors, straightforward configuration or syntax fixes, planned feature work, or broad architecture review. Diagnosis-only requests stop after reporting the root cause and evidence; apply a fix only when the user requested one.
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Write or edit Japanese articles, reports, guides, and public-facing drafts so the argument is clear and the prose reads naturally. Preserve the author's meaning, evidence, and voice when revising. Use for requests to write from a topic or notes, remove AI臭 / AIっぽさ, improve awkward wording or structure, or format notes as 箇条書き, チーム共有, 社内共有, a decision note, Slack post, or Teams post. For existing prose, ask Gemini through Antigravity CLI to rewrite naturally by default, then audit against the source; use the current model if unavailable. Do NOT use for handing work to another session (use my-handoff), ordinary Japanese answers, progress updates, technical explanations, code review, English-only prose that is not a bullet-formatting request, or an explicitly incompatible format.
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Manage Claude Code Viewer (CCV): preview in-progress CCV changes on ccv-preview, register HTML artifacts, download files, or schedule jobs via CCV local API. Use when user asks for CCV preview, ccv-preview, browser visual QA, UI/UX validation, CCV artifacts, CCV file download, or CCV scheduler jobs. Treat preview/プレビュー as the CCV app preview service first; use artifacts only when the user explicitly asks for artifact/dashboard/report HTML. Do NOT use for generic web app previews outside CCV, production deployment, Cloudflare config, or Anthropic remote triggers.
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Detects and prevents code injection attacks targeting serverless functions (AWS Lambda, Azure Functions, Google Cloud Functions) through event source poisoning, malicious layer injection, runtime command execution, and IAM privilege escalation via function modification. The analyst combines static analysis of function code, CloudTrail event correlation, runtime behavior monitoring, and IAM policy auditing to identify injection vectors across the expanded serverless attack surface including API Gateway, S3, SQS, DynamoDB Streams, and CloudWatch event triggers. Activates for requests involving Lambda security assessment, serverless injection detection, function event poisoning analysis, or serverless privilege escalation investigation.
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Deploys and configures Zeek (formerly Bro) network security monitor to passively analyze network traffic, generate structured logs, detect anomalous behavior, and create custom detection scripts for threat hunting and incident response.
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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.
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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.
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Detect RDP brute force attacks by analyzing Windows Security Event Logs for failed authentication patterns (Event ID 4625), successful logons after failures (Event ID 4624), NLA failures, and source IP frequency analysis.
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Detect and prevent QR code phishing (quishing) attacks that bypass traditional email security by embedding malicious URLs in QR code images within emails.
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Detects defense evasion techniques used by adversaries in endpoint logs including log tampering, timestomping, process injection, and security tool disabling. Use when investigating suspicious endpoint behavior, building detection rules for evasion tactics, or conducting threat hunting for stealthy adversary activity. Activates for requests involving evasion detection, defense evasion analysis, log tampering detection, or MITRE ATT&CK TA0005.
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Correlates disparate security incidents, IOCs, and adversary behaviors across time and organizations to identify unified threat campaigns, attribute them to common threat actors, and extract shared indicators for improved detection. Use when multiple incidents exhibit overlapping indicators, when sector-wide attack campaigns require cross-organizational analysis, or when building campaign-level intelligence products. Activates for requests involving campaign analysis, incident clustering, cross-organizational IOC correlation, or MISP correlation engine.
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Configures Microsoft Defender for Endpoint (MDE) advanced protection settings including attack surface reduction rules, controlled folder access, network protection, and exploit protection. Use when hardening Windows endpoints beyond default Defender settings, deploying enterprise-grade endpoint protection, or meeting compliance requirements for advanced malware defense. Activates for requests involving Windows Defender configuration, ASR rules, MDE tuning, or Microsoft endpoint security.
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Detect cyber attacks targeting OT historian servers (OSIsoft PI, Ignition, Wonderware) that sit at the IT/OT boundary and serve as pivot points for lateral movement between enterprise and control networks, including data manipulation, unauthorized queries, and exploitation of historian-specific vulnerabilities.
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Detect and test for OWASP API3:2023 Broken Object Property Level Authorization vulnerabilities including excessive data exposure and mass assignment attacks.
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This skill covers detecting cyber attacks targeting Supervisory Control and Data Acquisition (SCADA) systems including man-in-the-middle attacks on industrial protocols, unauthorized command injection into PLCs, HMI compromise, historian data manipulation, and denial-of-service against control system communications. It leverages OT-specific intrusion detection systems, industrial protocol anomaly detection, and process data analytics to identify attacks that traditional IT security tools miss.
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Detect container escape attempts in real-time using Falco runtime security rules that monitor syscalls, file access, and privilege escalation.
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