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概要と使いどころ
敵対的分析手法を統合したレビューの entry skill。認知バイアス対策の3手法 （Pre-mortem / War Game / Logic Torturing）と、宣言・主張と実態の乖離を突く claim-vs-actual 検出3パターン（Self-Contradiction / Refactor-Claim Audit / Cross-File Leakage）へルーティングし、通常のレビューでは見えない設計の盲点・ 防御の穴・論理の弱点・宣言と実装のズレを可視化する。
Creates and reviews agent skills safely by enforcing deletion-prevention harness rules: no fixed absolute temp paths, no cwd-dependent cleanup, no wildcard deletes, no workspace-external file operations, no silent cleanup failures, and mandatory temp-root validation before any destructive command. Use when creating a new skill, updating an existing SKILL.md, or reviewing prompts/runbooks that include temp files, extraction, cleanup, PowerShell, bash, rm, del, Remove-Item, or archive expansion.
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。
Enforces project coding standards during code review: naming conventions (PascalCase for classes, camelCase for methods/variables, UPPER_SNAKE_CASE for constants, kebab-case for files), standard file structure, anti-magic-number policy, file size limits (500/800 lines), security patterns, and design patterns. Use when reviewing code, writing new code, or checking adherence to project conventions.
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。
Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.
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。
Azure Data Lake Storage Gen2 SDK for Python. Use for hierarchical file systems, big data analytics, and file/directory operations.
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 Efs — aWS EFS file system management and performance analysis. Covers file system inventory, mount targets, access points, throughput modes, lifecycle policies, replication configurations, and storage metrics. Use when inspecting EFS file systems, debugging mount issues, reviewing performance settings, or optimizing storage costs.
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。
Store and retrieve unstructured objects, file uploads, and cache-like state on Netlify using the @netlify/blobs key/value API from Functions, Edge Functions, and Build Plugins. Use when a task involves saving user file or image uploads, persisting form or contact-form submissions, storing generated output from Background Functions (sitemaps/processed media/bulk-email results), building read-only asset stores, adding client-side blob expiration, or wiring file-based blob uploads at deploy time. Not for per-user, transactional, or relational data (counters/balances/sessions) — reach for Netlify DB there instead.
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。
SwiftUI ↔ Figma translation. Use whenever the user mentions Swift, SwiftUI, iOS, iPhone, or iPad — in EITHER direction — translating a Figma design into SwiftUI (design → code), or pushing SwiftUI views / screens / tokens back into a Figma file (code → design). Triggers on phrases like 'implement this Figma design in SwiftUI', 'build this screen in Swift', 'push this SwiftUI view to Figma', 'mirror my Swift code in a Figma file', or whenever a Figma URL appears alongside `.swift` files / an `.xcodeproj`. Routes to a direction-specific reference doc; loads alongside `figma-use` for the code → design path.
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。
Discover the user's local AWS context (active profile, region, account ID, caller identity) at the start of any AWS task. Use this skill before any other AWS work — deploying to SageMaker, creating resources, calling AWS APIs, or anything that touches an AWS account. Use it especially when the user has not specified a region or profile explicitly, when they say things like "use my AWS account", "deploy to AWS", "use my profile", or when about to make any AWS CLI or SDK call. Never guess the region or account ID — always use this skill to read it from the local configuration 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。
Create and edit JSON Canvas files (.canvas) with nodes, edges, groups, and connections. Use when working with .canvas files, creating visual canvases, mind maps, flowcharts, or when the user mentions Canvas files in Obsidian.
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。
Symbolicate .NET runtime frames in Apple platform .ips crash logs (iOS, tvOS, Mac Catalyst, macOS). Extracts UUIDs and addresses from the native backtrace, locates dSYM debug symbols, and runs atos to produce function names with source file and line numbers. Automatically downloads .dwarf symbols from the Microsoft symbol server using Mach-O UUIDs. USE FOR triaging a .NET MAUI or Mono app crash from an .ips file on any Apple platform, resolving native backtrace frames in libcoreclr or libmonosgen-2.0 to .NET runtime source code, retrieving .ips crash logs from a connected iOS device or iPhone, or investigating EXC_CRASH, EXC_BAD_ACCESS, SIGABRT, or SIGSEGV originating from the .NET runtime. DO NOT USE FOR pure Swift/Objective-C crashes with no .NET components, or Android tombstone files. INVOKES Symbolicate-Crash.ps1 script, atos, dwarfdump, idevicecrashreport.
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。
Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.
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。
Set up a complete CI/CD pipeline for a project. Detects the stack, then generates and validates GitHub Actions workflows, a Dockerfile, and a Makefile as one coherent pipeline. Use when asked to "set up CI", "add pipeline", "create GitHub Actions", "ci/cd setup", "automate builds", "containerize", or "add a Makefile".
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。
Generates as many digits of pi as possible and writes them into files inside a tokenMaxxing/ folder. Use when the user asks to token-maxx, fill a file with pi digits, test agent output throughput, or generate N pi files sequentially or in parallel.
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 drafting a bug or defect ticket, reviewing one someone else wrote, or deciding whether a reported problem is ready to file. Keeps what the reporter actually saw separate from what the agent later found out, so a reader can tell which lines are testimony and which are collected proof. Trigger phrases: 'file a bug', 'write up this defect', 'triage this report', 'is this ticket ready to file', 'what did the reporter actually see'.
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。
Azure Data Lake Storage Gen2 SDK for Python. Use for hierarchical file systems, big data analytics, and file/directory operations.
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。
Algorithmic philosophies are computational aesthetic movements that are then expressed through code. Output .md files (philosophy), .html files (interactive viewer), and .js files (generative algorithms).
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。
The AI native file format. EXIF for AI — stamps every file with trust scores, source provenance, and compliance metadata. Embeds into 20+ formats (DOCX, PDF, images, code). EU AI Act, SOX, HIPAA auditing.
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。
Search the documents uploaded for the CURRENT task/row (e.g. an Agentic Table row's attached files) via the `unique-cli uploaded-search "<query>"` command, with the same per-turn citation tracking as `unique-cli search` so cited facts render as `<sup>N</sup>` footnotes and clickable reference chips on the Unique platform. ALWAYS use this skill when the user refers to documents they uploaded/attached to this task, or when you need facts from the task's own attached files. These uploaded files are scoped to the chat, NOT to a knowledge-base folder, so they will NEVER appear in `unique-cli search` results no matter the folder or metadata filters. Use `unique-cli search` for the knowledge base and this command for the task's uploaded documents; the two are complementary and citation numbering is shared across them within a turn.
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。
Search the Unique AI Platform knowledge base using the unique-cli search command, with automatic per-turn citation tracking so cited facts render as clickable reference chips and `<sup>N</sup>` footnotes on the Unique platform. Use whenever the user asks to find, search, or query documents or content on Unique, including filtering by folder or metadata. Also covers `unique-cli read <cont_id>` for reading the full indexed text of a document when its content ID is already known. NOTE: This search uses combined vector + full-text indexing. Excel (.xlsx/.xls), CSV (.csv), and image files are NOT full-text indexed, so they will not appear in search results. To locate these file types, use the unique-cli-file-management skill instead (browse folders with `unique-cli ls` to find them 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。
Generates Nano Banana Pro prompts for profile icons and SNS images. Use when user mentions "プロフィール画像", "アイコン作成", "SNS用画像", or "ヘッダー画像".
Intelligent README.md generation prompt that analyzes project documentation structure and creates comprehensive repository documentation. Scans ./ directory files and creates a README.md file for the project. Only used when creating a new repository. or when the README.md file is missing.
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 the latest Claude (Anthropic), OpenAI Codex, and Google Gemini model releases from official primary sources, update model selections in this dotfiles repo, and update the Claude Code, Codex, and Gemini CLIs through their configured managers. Every run checks both the model settings and CLI for the selected provider, then scans the invoking repository for hardcoded model IDs. Use when the user asks to "モデル更新", "モデルを最新に", "最新モデル確認", "Codex/Claude Code/Gemini CLI本体の更新", "model bump", "update models", or "update agent CLIs". Do NOT use for one-off model selection in a single conversation, general model questions, or unrelated package updates.
Parse Windows LNK shortcut files to extract target paths, timestamps, volume information, and machine identifiers for forensic timeline reconstruction.
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。