「verification」の検索結果

Laravelの環境設定からコード検査、テスト、依存関係の脆弱性、データベース変更、キューまで順に確認し、マージやデプロイ前の問題を調べるスキル。

• Laravelのプルリクエスト前の確認
• 大きな改修や依存関係更新後の検証
• ステージング・本番へのデプロイ前確認

AIエージェントの反復作業を設計・点検し、機械で判定できる完了条件、変更禁止の境界、独立した検証、再試行上限を定めて空回りや暴走を防ぐスキル。

• 反復作業の完了条件を定めたいとき
• 空回りや検証の抜け道の点検
• 計画・実装・検証の役割分担

実際のメールボックスで受信メールの仕分け、返信の下書き、送信確認を進めるスキル。履歴と送信済みの記録を確かめ、使用アカウントや対応状況を明確にします。

• 受信箱の仕分けとアーカイブ候補整理
• 履歴を踏まえた返信を下書きしたいとき
• メールを送信して記録を確認したいとき

Djangoの公開や変更提案の前に、環境・コード品質・データベース変更・テスト・脆弱性・設定を順に検証し、段階別の合否と修正すべき問題をレポートにまとめます。

• Djangoの変更提案前の確認
• マイグレーションを確認したいとき
• テストカバレッジの目標確認

Cisco IOS／IOS-XEの設定をレビューし、通信の許可・拒否ルールやインターフェースの確認、障害調査用コマンドの選定、変更前後の検証を支援します。

• 変更前のルーター・スイッチ設定レビュー
• 読み取り専用コマンドで障害を調べたいとき
• ACLのマスクと適用方向の確認

AIエージェント専用のメール受信箱を用意し、送受信や返信、添付ファイルの処理を行います。メールで届く認証コードの確認や、受信をきっかけにした継続的な処理にも使えます。

• AIエージェント専用アドレスの作成
• メール送信と返信・添付ファイルの処理
• メールで届く認証コードの確認

Drive a real browser to inspect or interact with a web page or app — navigate, take screenshots, read console and network, fill simple forms — for verification tasks, not unattended automation.

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。

AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.

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。

Make scoped state changes with target confirmation, minimal mutation, and read-back verification

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。

AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.

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。

Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.

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。

Deliver a runnable local browser app so the user can operate it on the first handoff. This delivery skill does not choose whether a requested local system should be a browser app. On a current turn that explicitly says to implement a brand-new browser project now, load bundled:greenfield-project-scaffolding before project work only after no-peek or permitted top-level placement facts prove that no named or suitable current-folder target resolves the root; never hand off from planning or answer-only turns, existing work, a named or suitable target, or standalone or single-file delivery. Resolve user-blocking product or interface choices with an available interaction surface; resolving those choices alone never authorizes implementation. Always call read_skill for bundled:browser-app-delivery before creating or materially changing a local browser app that owns its start path or a playable browser game. Also load it when the user requests a paste-ready, single-file, offline, or immediately playable browser artifact, even if no local start path should remain, unless the user says they will open or check it themselves or explicitly declines verification. On completed local-server delivery, include exact start commands, a concrete local URL, and explicit browser-open wording. On completed standalone delivery, hand off the exact artifact path or paste URL and smoke result without inventing a server. Do not load it for a self-contained static file that has no owned start path if the user either says they will open or check it themselves or explicitly declines verification. Do not load it for component/style-only edits, deployed sites, backend/API-only work, browser QA, review, explanation, plan-only, or explicit stop/no-tool turns.

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。

XML-specified Android UI journey testing, interactive step execution, assertion verification, and JSON outcome reporting.

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。

Automated end-to-end UI testing and verification on an Android Emulator using ADB.

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。

Three-layer verification pipeline for AI output. Extracts verifiable claims, finds supporting or contradicting sources via web search, runs adversarial review for hallucination patterns, and produces a structured verification report with source links for human 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。

Create forensically sound bit-for-bit disk images with dd or dcfldd on a Linux forensic workstation, preserving evidence integrity through hash verification (MD5/SHA) during acquisition. Use when imaging a suspect drive, USB device, or memory card for investigation, preserving volatile disk evidence during incident response, or producing a verified copy for legal or law-enforcement proceedings before any destructive 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。

Ingest meeting transcripts from ANY meeting recorder into brain pages with attendee enrichment, entity propagation, and timeline merge. One unified pipeline: normalize the source into a standard transcript record, split multi-meeting recordings, resolve speakers by evidence, create the page, pass every surprising claim through the consistency check (transcript + brain + plausibility), enrich every entity, then run the verification checklist — substance AND sequence. A meeting is NOT fully ingested until the enrich skill has processed every entity AND the verification checklist passes, including the sequence verify (PASS or explicit user waive).

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。

CAPA system management for medical device QMS. Covers root cause analysis, corrective action planning, effectiveness verification, and CAPA metrics. Use when running CAPA investigations, 5-Why analysis, fishbone diagrams, root cause determination, corrective action tracking, effectiveness verification, or CAPA program optimization.

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。

Real Chrome/Brave + macOS Computer Use from inside the browser — zero CDP fingerprint, real sessions; mandatory for visual deploy verification. Drive clickwork yourself. USE WHEN verify deploy, confirm UI, screenshot verification, computer use, macos automation, debug web, troubleshoot, visual check, motion/animation bug, jank, transition stutter, scrub a flow, console logs/errors, runtime/JS/react errors, mismatch warning, network traffic/log, HAR/pcapng export, hydration/blank-page debug, flash then blank/page broken, why is this not working/what's happening on the page, authenticated page, bot detection bypass, reproduce bug, drive native app, about to ask the operator to click/navigate/fill a form/log in/approve OAuth, OAuth consent flow, complete a web login, do this in your browser. NOT FOR residential-proxy crawling (BrightData) or social actor scraping (Apify).

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。

Rigorous mathematical proof verification and fixing workflow. Reads a LaTeX proof, identifies gaps via fresh-agent Codex GPT-6-Astra ultra review, fixes each gap with full derivations, re-reviews, and generates an audit report. Base review is same-family provisional. Use when user says "检查证明", "verify proof", "proof check", "审证明", "check this proof", or wants rigorous mathematical verification of a theory paper.

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。

Rigorous mathematical proof verification and fixing workflow. Reads a LaTeX proof, identifies gaps via cross-model review (external reviewer backend, ultra reasoning), fixes each gap with full derivations, re-reviews, and generates an audit report. Use when user says "检查证明", "verify proof", "proof check", "审证明", "check this proof", or wants rigorous mathematical verification of a theory paper.

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 about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

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。

When the user wants to build data enrichment workflows, score leads against ICP, set up Clay waterfalls, or improve contact data quality. Also use when the user mentions 'enrichment,' 'data enrichment,' 'Clay,' 'waterfall enrichment,' 'ICP scoring,' 'lead scoring,' 'intent data,' 'contact verification,' 'Apollo,' 'ZoomInfo,' or 'data quality.' This skill covers lead enrichment waterfalls, ICP scoring frameworks, and contact verification systems. Do NOT use for technical implementation, code review, or software architecture.

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。

Apply a prompt-agnostic execution and verification loop to any substantial task while preserving the original request. Use when the user asks to fan out work, use subagents or independent reviewers, loop until done, benchmark against references, apply a harsh critic, compare candidates blind, improve an existing prompt with verification, or continue until explicit quality gates pass.

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。