3,080 件 ・ 関連度順
概要と使いどころ
Draft and review social outreach with Guaardvark's supervised outreach system (Reddit, Discord, Twitter/X, Facebook): grounded, graded drafts that never post without the user's approval in the Studio. Use when the user wants a reply drafted for a thread, wants to see the pending outreach queue, or asks about outreach status or cadence.
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 diagrams, flowcharts, and conceptual illustrations using OpenAI gpt-image-2 (default) or gpt-image-1. Use for: algorithm/code flow diagrams, system architecture sketches, conceptual illustrations, and any figure that does NOT represent actual code execution output (data plots, model results, etc. must still be generated by running Python code). Requires OPENAI_API_KEY and OpenAI organization verification when used from Claude Code / API path. OpenAI Codex subscribers can use built-in $imagegen without an API key.
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。
Assign, validate, normalize, and explain Luhmann/Zettelkasten-style project-note codes for Chinese book manuscripts, Obsidian Markdown folders, Mandala-Grid section files, HyperCard Markdown stacks, and project-note JSON to EPUB workflows. Use when Codex needs to scan folders for 部/章/節/項/目 numbering, generate stable card ids, insert branch codes without renumbering existing notes, map letter-coded branches to Obsidian Mandala sections, preserve K### keyword index cards, sanitize private catalogs into public examples, or prepare card IDs for EPUB and HyperCard output.
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 formal verification artifacts (Isabelle, Coq, Dafny, etc.) and produce structured reports identifying the precise boundary between verified, assumed, and unverified components. Use when assessing verification coverage, understanding trust boundaries, auditing formal proofs, or documenting verification scope. Reports explicitly list verified code, assumptions, axioms, trusted computing base, and unverified components. Conservative and explicit about verification status without attempting to repair or mask 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。
Restructure and improve Isabelle or Coq proofs to enhance readability, modularity, and maintainability without changing semantics. Use when proofs are long and monolithic, have repeated patterns, use unclear naming, lack documentation, or when the user asks to refactor, clean up, improve, or reorganize their formal proofs.
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。
Creates structured context summaries for continuing work across AI sessions. Use when ending a session to enable seamless continuation in a new session without losing 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。
Generate test cases using metamorphic testing by applying transformations based on metamorphic properties. Use when you need to expand test suites, test programs without oracles, validate mathematical or algorithmic properties, or detect subtle bugs through input-output relationships. The skill takes a program, original test cases, and metamorphic properties as input, generates new test cases by applying transformations, executes tests, verifies outputs satisfy properties, reports violations and anomalies, and outputs an expanded test suite with property coverage summary. Supports multiple programming languages and property types.
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。
Designer-turned-developer who crafts stunning UI/UX even without design mockups. Use for any frontend implementation requiring visual design decisions, aesthetic direction, or pixel-perfect UI work.
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。
Automatically identify metamorphic properties (symmetry, linearity, additivity, input invariances) from programs or functions. Use when generating metamorphic tests, discovering program properties, validating transformations, or creating test oracles without explicit specifications. Analyzes control flow, data flow, and sample executions to output structured properties for metamorphic test generation and 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。
Generate test assertions from existing code implementation. Use when the user has implementation code without tests or incomplete test coverage, and needs assertions synthesized by analyzing the code's behavior, inputs, outputs, and state changes. Supports Python (pytest/unittest), Java (JUnit/AssertJ), and JavaScript/TypeScript (Jest/Chai). Handles equality checks, collections, exceptions, and state 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。
Performs abstract interpretation to produce summarized execution traces and high-level program behavior representations. Highlights key control flow paths, variable relationships, loop invariants, function summaries, and potential runtime states using abstract domains (intervals, signs, nullness, etc.). Use when analyzing program behavior, understanding execution paths, computing loop invariants, tracking variable ranges, detecting potential runtime errors, or generating program summaries without concrete execution.
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 and inspect the installed Blueish Blender Asset Library without mutating it. Use when a user asks for a local Blender asset, node preset, Blueish asset, Asset Browser entry, or named source, or when the Router has selected a node-centric/reusable Geometry Nodes, material, simulation, rigging, compositor, or NPR route with eligible local catalogs; return compatible, attributable candidates for the Router-approved 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。
Build and validate Blender 5.2 Cycles 3D-to-2D materials using four camera-plane-offset Shader Raycast tests to derive an editable silhouette mask, combined with Cycles-compatible toon or flat shading. Use when a Cycles render needs an in-material outline without Shader to RGB.
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。
Plan, build, place, and validate physically meaningful Blender object assemblies, including manufactured part boundaries, mechanical seams, mounting interfaces, pivots, hierarchy, constraints, instancing, modular grids, connector planes, and precision snapping. Use when several objects must form one product, machine, architectural module, vehicle, furniture item, mechanism, or environment structure without incorrectly welding independent parts, eyeballing alignment, or leaving continuous shells as overlapping primitives.
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 self-contained interactive HTML dashboards with Chart.js, dropdown filters, and professional styling. Use when creating dashboards, building interactive reports, or generating shareable HTML files with charts and filters that work without a server.
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。
Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
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 institutional-grade comparable company analyses with operating metrics, valuation multiples, and statistical benchmarking in Excel/spreadsheet format. **Perfect for:** - Public company valuation (M&A, investment analysis) - Benchmarking performance vs. industry peers - Pricing IPOs or funding rounds - Identifying valuation outliers (over/under-valued) - Supporting investment committee presentations - Creating sector overview reports **Not ideal for:** - Private companies without comparable public peers - Highly diversified conglomerates - Distressed/bankrupt companies - Pre-revenue startups - Companies with unique business models
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。
Simplify existing code for clarity and maintainability without changing behavior. Use when asked to clean up or simplify code, especially recent changes.
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, edit, or composite images with Gemini/Nanobanana. Default for image requests without a named provider; do not override a different provider the user chose.
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。
An engineering-grade marketing system organized around two surface modes — a deep black canvas for hero and footer chapters and a flat paper-white canvas for body content — connected by a single, almost violently saturated NVIDIA Green accent that carries every CTA, every active tab, and the small decorative corner squares that mark out cards. The system is unapologetically angular: 2px radius across every surface, tight bold sans-serif typography in NVIDIA's proprietary EMEA cut, and a hairline gray rule that separates dense multi-column technical content. There is no decorative gradient, no atmospheric mesh, no soft drop shadow — just black, white, gray, and green stacked into a structured editorial grid that scales from product cards to massive industry landing pages without bending its rules.
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 for writing, reviewing, debugging, or testing Pandera schemas and runtime validation for Polars DataFrame or LazyFrame pipelines installed with pandera[polars]. Trigger on pandera.polars DataFrameSchema, DataFrameModel, Column, Field, Check, PolarsData, decorators, coercion, strictness, lazy error collection, and validation-depth decisions. Do not use for pandas-backed Pandera, Pydantic object models, Polars transformations without Pandera, static dataframe typing alone, or generic data-quality 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。
Verify fix commits address audit findings without new bugs
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。
Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies for lean, fast execution.
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 the user wants Hermes Agent to build, refine, test, or validate a CLI-Anything harness for a GUI application or source repository. Adapts the CLI-Anything methodology to Hermes without changing the generated Python harness format.
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。