「what」の検索結果

TypeScriptとNative markupでデスクトップアプリを作るための導入ガイド。ひな形作成、画面実装、配布、動作確認に必要なNative SDKの手順へ案内します。

• デスクトップアプリを作り始めたいとき
• ネイティブ画面の実装手順を探したいとき
• 既存のWeb画面を組み込みたいとき

ダッシュボードの目的から各パネルの表示内容、データ取得元、更新頻度までを整理するスキル。画面操作や外部連携の仕様も含め、設計資料にまとめます。

• ダッシュボードの要件を固めたいとき
• 各パネルのデータ元と更新頻度の整理
• 画面操作や外部連携の仕様を決めたいとき

検索ツールの失敗が続くとき、再試行を続けるか既存知識で文書作成へ進むかを判断します。エラーの種類と連続失敗回数を確認し、外部検証できなかった情報や理由を記録します。

• 検索エラーが続いた後の方針判断
• 既存知識で技術文書の草稿作成
• 外部検証できなかった情報の記録

保存済みのExcelファイルをPythonで直接検査し、シート名・行数・マーク済み行・出力の有無を確認。エージェントの報告との食い違いを調べるスキル。

• エージェントの表計算報告を照合したいとき
• 編集結果が保存されたか確認したいとき
• マーク済み行を正確に数えたいとき

Web検索が繰り返し失敗した際に、既存知識で作業を続けられるか判断し、未確認の主張や情報の確度を示して、後から確認する項目をまとめるスキル。

• 検索なしで作業を続けられるか判断したいとき
• 検索障害中に既存知識で下書きしたいとき
• 未確認の主張や情報の確度を示したいとき

PDF抽出や検索などのツールが繰り返し失敗した際に、原因と未完了の作業を整理します。限界を明記した部分成果と、再開や人への引き継ぎに必要な次の手順を示すスキルです。

• PDF抽出の失敗状況を報告したいとき
• 信頼性を明記して調査途中の成果を出す
• 停止した作業を人に引き継ぎたいとき

Measures and interprets what a fuzzing campaign actually reaches, using llvm-cov, lcov, or a fuzzer's own coverage output. Covers baselining a new campaign, reading coverage reports, and turning uncovered regions into harness, seed, or dictionary work. Use when a fuzzer plateaus, when judging whether a harness is effective, after changing a harness, or when asking why some code is never reached.

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。

Designs and improves fuzzing harnesses for C/C++ and Rust. Covers mapping raw bytes onto a target API, generating structured inputs, avoiding non-determinism and false crashes, and deciding what to fuzz together. Use when writing a first LLVMFuzzerTestOneInput or fuzz_target! harness, when a campaign finds nothing or reports crashes that will not reproduce, or when the target API needs structured rather than raw input.

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。

Compares Trailmark code graphs at two source code snapshots (git commits, tags, or directories) to surface security-relevant structural changes. Detects new attack paths, complexity shifts, blast radius growth, taint propagation changes, and privilege boundary modifications that text diffs miss. Use when comparing code between commits or tags, analyzing structural evolution, detecting attack surface growth, reviewing what changed between audit snapshots, or finding security-relevant changes that text diffs miss.

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。

Draws the 12 Houses of the Zodiac Tarot spread to inject entropy into planning when prompts are vague, ambiguous, or casually delegated. Interprets the spread to guide next steps. Use when the user says 'let fate decide', 'YOLO', 'whatever', 'idk', or other nonchalant phrases, makes Yu-Gi-Oh references, or when you are about to arbitrarily pick between multiple reasonable approaches. Prefer over asking clarifying questions when the user's tone is casual or playful rather than precision-seeking.

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。

Interprets Culture Index (CI) surveys, behavioral profiles, and personality assessment data. Supports individual profile interpretation, team composition analysis (gas/brake/glue), burnout detection, profile comparison, hiring profiles, manager coaching, interview transcript analysis for trait prediction, candidate debrief, onboarding planning, and conflict mediation. Accepts extracted JSON or PDF input via OpenCV extraction script. Use when the user shares a Culture Index PDF or JSON profile, asks what someone's CI traits mean, compares Culture Index profiles across a team or against a hiring profile, or asks about burnout risk from Survey-versus-Job gaps.

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。

Check code against the documentation that specifies it - which requirements hold, which the code contradicts, which are absent, and what the code does that no document mentions. Use when comparing an implementation against a whitepaper, protocol spec, or design document.

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。

Performs security-focused differential review of code changes. Adapts analysis depth to codebase size, uses git blame for context, calculates blast radius by counting callers, checks test coverage of modified code, and generates a markdown report. Use when reviewing a PR, commit, or diff for security vulnerabilities, checking whether a change re-introduces a previously fixed bug, asking what else a change could break, or finding which modified code has no test covering it.

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。

Penetration test and red team report writing methodology. Covers executive summary structuring (risk-led narrative for non-technical readers), technical finding format (title, severity, affected scope, narrative, reproduction steps, impact, remediation, references), CVSS v3.1 / v4.0 scoring with vector justification, OWASP risk rating, evidence hygiene (redacting credentials, hashing client data, time-stamping every action), screenshot and PoC artifact management, finding chain narratives, scope/limitations/assumptions documentation, retest evidence and remediation tracking, deliverable formats (PDF, DOCX, HTML, JSON for SIEM ingestion), client-customer-deliverable separation, and common report mistakes (over-CVSSing, undermining the triager, missing the 'so what'). Use at the end of an engagement when authoring a deliverable, when restructuring a draft for executive readability, or when establishing a reusable report template for a consulting practice.

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 API security testing methodology covering REST, gRPC, and WebSocket attack surfaces. Addresses the full OWASP API Security Top 10 2023 including BOLA/IDOR, broken authentication, excessive data exposure, rate limiting bypass, BFLA, mass assignment, SSRF, and security misconfiguration. Includes REST-specific attacks such as HTTP verb tampering, content-type switching, and parameter pollution. Covers gRPC exploitation through protobuf interception, reflection API enumeration, and metadata injection. Addresses WebSocket vulnerabilities including origin bypass, message injection, and cross-site WebSocket hijacking. Provides tooling guidance for Burp Suite, Postman, grpcurl, websocat, and mitmproxy. Each technique includes detection signatures and defensive indicators so you understand what artifacts your testing leaves behind. Designed for authorized penetration testing engagements against API-driven architectures.

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。

Build a threat model for a target codebase. Three modes: "interview" walks an application owner through the four-question framework and produces a threat model from their answers; "bootstrap" derives a threat model from the code plus past vulnerabilities (CVEs, git history, pentest reports) when no owner is available; "bootstrap-then-interview" chains the two when both owner and codebase are present. All write THREAT_MODEL.md in a shared schema. Use when asked to "threat model", "build a threat model", "map the attack surface", or "what should we be worried about in this codebase".

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。

Triage a batch of raw security findings. Verify each is real, collapse duplicates, re-rank by derived exploitability, and tag with an owner. Takes a directory or file of scanner output and writes TRIAGE.json + TRIAGE.md sorted by what actually needs engineering attention. Use when asked to "triage findings", "validate scanner output", "prioritize vulns", or "review the backlog". Runs interactively by default; pass --auto to skip the interview.

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。

Evaluate a local Codex plugin in engineer-friendly language. Use when the user says "evaluate this plugin", "audit this plugin", "why did this score that way", "what should I fix first", "help me benchmark this plugin", or asks for a plugin-wide report before comparing versions.

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。

Turn plugin-eval findings into a concrete rewrite brief for a Codex skill. Use when the user already evaluated a skill and now wants Codex to improve it, especially after asking what to fix first.

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。

Evaluate a local Codex skill in engineer-friendly terms. Use when the user says "evaluate this skill", "give me an analysis of the game dev skill", "audit this skill", "why did this score that way", "what should I fix first", or asks for a skill-specific report before benchmarking it.

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。

Load or manage Product Design's saved user context. Use when the user asks to set up Product Design, get started, onboard, save product or design sources, see what Product Design remembers, update saved context, or remember Product Design preferences. Examples include product URLs, Figma files, screenshots, reference images, codebase paths, Storybook, tokens, design systems, brand assets, and general product/design notes.

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。

Analyze product or business data to support a decision or recommendation. Use when a decision depends on metric-backed evidence, such as choosing a direction, prioritizing an opportunity, evaluating a change, segmenting users, sizing tradeoffs, or deciding what to do next.

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。

Implement reviewer feedback on a Canva design. Reads all comment threads, synthesises what reviewers want, makes the clear-cut changes directly, and flags anything that needs a human decision. Use when the user asks to "implement feedback on my deck", "address comments on a design", "apply review feedback", "fix the comments on my presentation", or "implement the feedback".

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 Creative Production is explicitly invoked or mentioned without a concrete request, when the user asks what Creative Production can do, or when the user wants help getting started without enough context to choose a 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。