260 件 ・ 関連度順
概要と使いどころ
Architecture Patterns workflow skill. Use this skill when the user needs Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
Architecture Patterns workflow skill. Use this skill when the user needs Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
Specialized visual and multimedia processing tools. Use this skill whenever a task involves complex visual content — UI mockups, dense screenshots, design images, charts, artwork — where precise details like spacing, hex colors, font sizes, and component hierarchy need to be extracted accurately. Also use for: reviewing or auditing existing UI against designs, comparing screenshots for visual regressions, transcribing audio/video, extracting data from PDFs with complex layouts, and generating images. Trigger whenever the user wants to implement from a design, review or compare UI screenshots, analyze visual details precisely, describe artwork or aesthetic content, or process any media file (audio, video, PDF).
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 adding a use case, port, repository or adapter in a Go service — where each piece goes, how errors and transactions cross layers, and how to check the import direction
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 starting a new Spring Boot 4 project — scaffolding a service, REST API, or modular backend; picking an architecture (layered, package-by-module, modular-monolith, tomato, DDD-hexagonal); selecting Spring Boot 4 features; or applying the bundled templates and references in this skill. Not for migrating existing projects or for isolated JPA/repository work without broader project-creation context.
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。
Encode and decode raw Hyperlane messages to/from packed hex bytes using the CLI. Use when you need to construct a message for testing, inspect a raw message from logs or a transaction, or decode a warp transfer body.
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。
Audit existing color usage in a codebase — find inconsistencies, hardcoded values, and contrast failures. Use when asked to "audit our color usage", "find hardcoded hex values", or "check for contrast failures".
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。
Software design principles, patterns, and architecture from SOLID through distributed systems. Covers the five SOLID principles with violations and fixes, DRY/KISS/YAGNI heuristics, separation of concerns, 12 GoF design patterns organized by intent (creational, structural, behavioral), architectural patterns (MVC, MVP, MVVM, layered, hexagonal, microservices, event-driven), coupling and cohesion metrics, dependency injection, and the design decision framework for choosing between competing approaches. Use when making design decisions, reviewing architecture, refactoring code, or teaching software engineering principles.
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 this skill whenever the user wants to analyze binaries with radare2/r2 from the command line, including reverse engineering, disassembly, function analysis, strings/import inspection, patching, binary diffing, hex inspection, or r2 scripting. Also use it when the user mentions PE/ELF/Mach-O/DEX/WASM files together with CLI analysis, `rabin2`, `rasm2`, `radiff2`, `r2pipe`, or asks for radare2 command help on Windows/Linux/macOS.
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。
Analyzes a Stitch project's screens and synthesizes a natural-language DESIGN.md — visual atmosphere, color palette with hex values, typography rules, and Stitch-ready prompt snippets. Use this before stitch-loop or any multi-page build to establish design consistency.
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。
Backend conventions and patterns. Use when working on API routes, dependency injection, or hexagonal architecture in the backend.
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。
Generate jigsaw puzzles via generate_puzzle() or geom_puzzle_*() with parameter validation against inst/config.yml. Supports rectangular, hexagonal, concentric, voronoi, and snic puzzle types with configurable grid, size, seed, offset, and layout parameters. Use when creating puzzle SVG files for a specific type and configuration, testing generation with different parameters, generating sample output for documentation or demos, or creating ggplot2 puzzle visualizations.
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。
Epistemic transparency — acknowledging uncertainty, flagging limitations, avoiding overconfidence, and communicating what is known, unknown, and uncertain with proportional confidence. Maps the HEXACO personality dimension to AI reasoning: truthful calibration of confidence, proactive disclosure of gaps, and resistance to the temptation to appear more certain than warranted. Use before presenting a conclusion, when answering questions where knowledge is partial or inferred, after noticing a temptation to state uncertain information as certain, or when a user is making decisions based on provided information.
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。
Identify insects using body plan analysis, dichotomous keys to order, wing venation, mouthpart type, antennae form, leg and tarsal structure, and confidence levels. Covers the fundamental hexapod body plan verification, a simplified dichotomous key to major orders, wing venation and type analysis, mouthpart classification, antennae morphology, leg specialization and tarsal formula, and a structured confidence assessment framework. Use when you need to identify an unknown insect beyond preliminary order placement, are working through a specimen for taxonomic study, want to distinguish between similar orders or families, or need to assign a confidence level to a field identification.
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。
Server-Side Request Forgery (SSRF) occurs when user-controlled input is used to construct URLs that the server fetches, enabling access to internal services, cloud metadata endpoints (169.254.169.254), and local files via `file://` scheme. Detect via parameters accepting URLs or hostnames, PDF/report generators rendering `<iframe>/<img>/<script>`, and blind SSRF via out-of-band DNS callbacks. Bypass filters using IP decimal/octal/hex encoding, URL-userinfo tricks, and URL fragments. Tools: Burp Collaborator, curl.
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。
Tunes noisy detections by analyzing historical alert data to quantify false-positive sources, recommend allow-list filters and threshold adjustments, and measure precision impact. Activates for requests to tune a detection, reduce false positives, or analyze alert noise and recommend filters.
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。
Reverses proprietary command-and-control protocols: locating send/recv routines, recovering the message framing and encryption/encoding, and reconstructing the command set to build a decoder or emulator. Activates for requests to reverse a custom C2 protocol, decode beacon traffic, or document a malware command structure.
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。
Identifies and unpacks packed binaries: detecting packers from section names and entropy, automatically unpacking UPX, and manually unpacking custom packers by finding the OEP and dumping. Activates for requests to unpack a packed sample, detect a packer, or recover the original binary from UPX or a custom packer.
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。
Reverse engineers malware written in less-common compiled languages (Nim, Crystal, V, Zig, D) by detecting language-specific runtime signatures, name-mangling, and runtime strings to orient analysis. Activates for requests to reverse Nim malware, identify the source language of an exotic binary, or analyze Crystal/V/Zig/D compiled samples.
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。
Validates detection coverage by mapping Atomic Red Team tests to ATT&CK techniques, checking which of your detections cover each tested technique, and reporting coverage gaps. Activates for requests to validate detections with atomic tests, map Atomic Red Team to coverage, or find detection gaps against tested techniques.
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。
Analyzes position-independent shellcode: disassembling raw bytes at the right architecture, recognizing PEB-walk API resolution and egg hunters, and emulating execution to recover behavior and payloads. Activates for requests to analyze shellcode, disassemble raw position-independent code, or emulate a shellcode blob.
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。
Uses YARA to classify and triage samples at scale: applying rule sets, reading matches and string offsets, tuning for false positives, and organizing rules for malware family identification. Activates for requests to scan files with YARA, apply YARA rules, or classify samples by signature.
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。
Expands one indicator into the full scope of an incident: pivoting across data sources to find related hosts, accounts, and infrastructure, building a timeline, and bounding what is and is not affected. Activates for requests to scope an incident, pivot from a single IOC, or determine the blast radius of a 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。
Structures a clear, actionable malware analysis report covering summary, sample identity, capabilities, IOCs, ATT&CK mapping, and detection guidance for both technical and decision-making audiences. Activates for requests to write, structure, or review a malware analysis or reverse-engineering report.
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。