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概要と使いどころ
Cross-session progress tracking, pattern extraction, and session resumption. Gives agents memory across sessions using markdown files in `.memory/pipeline/progress/`. Subsumes self-improving-agent — handles both implementation tracking AND experiential learning in one skill. Workflows invoke specific protocols by name.
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。
Knowledge graph and smart memory management using graphify + Obsidian-inspired patterns. Use when: setting up a knowledge graph, managing memory health, cross-linking notes, compiling wiki pages from scattered notes, adding structured frontmatter, or running memory health checks. Triggers on: 'knowledge graph', 'graphify', 'wiki', 'cross-link', 'memory health', 'frontmatter', 'compile notes', 'wikilinks'.
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 working with Azure Lighthouse — azure Lighthouse delegated resource management. Covers delegation assignments, managed service offers, customer tenant access, cross-tenant resource visibility, role assignments, and delegation auditing. Use when managing multi-tenant Azure environments, reviewing delegated access, auditing cross-tenant permissions, or configuring managed service registrations.
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 working with Aws Service Catalog — aWS Service Catalog portfolio and product management. Covers portfolio administration, product versioning, provisioned product inspection, launch constraints, tag options, and sharing across accounts. Use when managing self-service IT catalogs, provisioning products, reviewing portfolios, or auditing product usage across an organization.
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 demos and GPU compute with Gradio Spaces and Hugging Face Spaces ZeroGPU. Use when writing or reviewing code that uses `@spaces.GPU`, configuring `python_version` or `requirements.txt` for a ZeroGPU Space, or handling ZeroGPU-specific code constraints — pickle-based process isolation, `gr.State` semantics across the worker boundary, no `torch.compile` (use AoTI instead), CUDA wheel-only builds (no `nvcc` at build or runtime), large vs xlarge sizing, and dynamic duration callables. Make sure to use this skill whenever the user mentions ZeroGPU, `@spaces.GPU`, or the `spaces` Python package, or hits ZeroGPU-specific code errors like `PicklingError` across the worker boundary, `illegal duration`, or `flash-attn` wheel-build failures — even when the user does not explicitly ask for ZeroGPU coding guidance. Trigger on `import spaces` or `@spaces.GPU` in code.
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。
DeFi Specialist IA — Expert en finance décentralisée (Uniswap, Aave, Compound, liquidity pools, yield farming, impermanent loss)
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。
Patterns for managing MSBuild item groups: Include/Remove/Update semantics, item metadata, batching with %(Metadata), transforms, per-item filtering, and cross-product batching pitfalls. Only activate in MSBuild/.NET build context. USE FOR: diagnosing and fixing item group anti-patterns in .csproj files, reviewing item management for correctness, fixing CS2002 duplicate file warnings from SDK globbing, fixing targets that run more times than expected due to cross-product batching, fixing Include vs Update misuse on SDK-globbed items, fixing FileWrites registration for generated file clean support, moving generated files to IntermediateOutputPath. DO NOT USE FOR: target chain architecture (use target-authoring), property patterns (use property-patterns), incrementality (use incremental-build), general anti-patterns (use msbuild-antipatterns), non-MSBuild build systems.
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。
Pull design principles from architecture, fashion, film, industrial design, and physical spaces into screen-based design. Use when seeking inspiration beyond digital, expanding creative range, or building cross-disciplinary design vocabulary.
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。
Core Swift development workflows for Xcode and Swift tooling, including project setup, dependency management, concurrency guidance, language/runtime best practices, and troubleshooting build or package resolution issues. Use when working on Swift tasks across a codebase, especially package/tooling/runtime work and cross-cutting Swift conventions (mutation semantics, naming, enum/file rules, import hygiene), including in SwiftUI projects.
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 working with iOS/macOS Keychain Services (SecItem queries, kSecClass, OSStatus errors), biometric authentication (LAContext, Face ID, Touch ID), CryptoKit (AES-GCM, ChaChaPoly, ECDSA, ECDH, HPKE, ML-KEM), Secure Enclave, secure credential storage (OAuth tokens, API keys), certificate pinning (SecTrust, SPKI), keychain sharing across apps/extensions, migrating secrets from UserDefaults or plists, or OWASP MASVS/MASTG mobile compliance on Apple platforms.
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。
Adapt designs to work across different screen sizes, devices, contexts, or platforms. Implements breakpoints, fluid layouts, and touch targets. Use when the user mentions responsive design, mobile layouts, breakpoints, viewport adaptation, or cross-device compatibility.
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。
This skill should be used when the user asks to "test for XSS vulnerabilities", "perform cross-site scripting attacks", "identify HTML injection flaws", "exploit client-side injection vulnerabilities", "steal cookies via XSS", or "bypass content security policies". It provides comprehensive techniques for detecting, exploiting, and understanding XSS and HTML injection attack vectors in web 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。
Expert security auditor for AI Skills and Bundles. Performs non-intrusive static analysis to identify malicious patterns, data leaks, system stability risks, and obfuscated payloads across Windows, macOS, Linux/Unix, and Mobile (Android/iOS).
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。
Implementing Cloud Data Loss Prevention (DLP) using Amazon Macie, Azure Information Protection, and Google Cloud DLP API to discover, classify, and protect sensitive data across cloud storage, databases, and data pipelines.
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。
Tespit etme compromised cloud credentials across AWS, Azure, and GCP by analyzing anomalous API activity, impossible travel patterns, unauthorized resource provisioning, and credential abuse indicators using GuardDuty, Defender for Identity, and SCC Event Threat Tespit.
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。
係数全開示型のOSS（オープンソース）AVM、「AVM界のLinux」を目指す土地査定エンジン。日本の土地（更地・所有権）の査定価格をMLIT取引事例から統計的に算定する白箱AVMスキル。媒介査定・売却価格の検討・お客様への査定書作成・相場確認・取引事例比較・比準価格算定・公示価格との比較など、土地の価格を客観的かつ説明可能な形で出したい時は、ユーザーが「ヘドニック」「回帰」「白箱」と言わなくても必ずこのSkillを使うこと。トリガー語例：「土地の査定」「土地査定して」「査定書を作って」「査定書がほしい」「いくらで売れる」「売却価格」「査定価格」「相場感」「相場を出して」「マーケット価格」「取引事例から」「事例比較で」「比準価格」「公示価格と比べて」「お客さんに渡す査定書」「顧客提示用の資料」「土地価格査定クン」「土地査定クン」「重調クンの土地版」「説明できる査定」「根拠付きで査定」「AVM」「自動査定」「鑑定書ではなく査定書として」など。MLIT取引価格情報CSV と地価公示GeoJSON（L01）を入力に（基準地価は不可）、ヘドニック係数を都度回帰で算定して個別格差補正を全開示する白箱AVM方式で、業者用シート（係数全開示）と顧客用シート（流推方式準拠）の2シート構成xlsxを出力する。マンション・戸建（建物含む）・借地権・地上権は対象外。
ScalarDBサイジング見積もりエージェント - Enterprise/OSSエディション別のインフラ構成・Pod数・コストを対話形式で見積もり。/scalardb-sizing-estimator で呼び出し。
ScalarDBエディション選定エージェント - 対話形式で最適なScalarDBエディション（OSS/Enterprise Standard/Premium）を選定。/select-scalardb-edition で呼び出し。
Social media command desk (Busabase App-in-Skill) for Kelly's Twitter/X, Facebook, and Instagram accounts (extensible to LinkedIn, YouTube, Threads, TikTok, Xiaohongshu), covering cross-platform monitoring and ECHO-based publishing. Use when the user invokes $kelly-social or /kelly-social, wants cross-platform account metrics and timelines, or needs a content calendar, draft review, engagement inbox, crisis playbook, share-of-voice, or pre-publish quality gate.
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。
Kelly Ecommerce Intel: App-in-Skill daily industry intelligence cockpit for e-commerce and cross-border sellers (Busabase App-in-Skill). Use when the user asks about e-commerce, cross-border selling, product trends, competitor prices, listing optimization, ads,电商, or跨境 scenes. Prepares news/source signals, buyer-intent interpretation, approved sales actions, and channel drafts for review before any external handoff.
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 asked to map, crosswalk, align, compare, or gap-analyze any two cybersecurity frameworks, control catalogs, or regulatory requirements using NIST IR 8477 Set-Theory Relationship Mapping (STRM). Triggers on terms like "map controls", "crosswalk", "framework alignment", "gap analysis", or producing a STRM CSV output file.
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 OAuth access token theft and misuse by analyzing sign-in logs for impossible travel, new device patterns, token replay from unusual IPs, and anomalous scope requests via Microsoft Graph and Okta APIs.
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。
Detecting compromised cloud credentials across AWS, Azure, and GCP by analyzing anomalous API activity, impossible travel patterns, unauthorized resource provisioning, and credential abuse indicators using GuardDuty, Defender for Identity, and SCC Event Threat Detection.
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。
Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms. Saves to UBIQUITOUS_LANGUAGE.md. Use when user wants to define domain terms, build a glossary, harden terminology, create a ubiquitous language, or mentions "domain model" or "DDD".
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。