2,634 件 ・ 関連度順
概要と使いどころ
Designing the household as an operating system. Covers room-function mapping, work-triangle analysis, storage topology, utility flow, and the Richards/Beecher lineage that treats the home as an engineered environment rather than a stage set. Use when planning a new kitchen, reorganizing a room, diagnosing friction in a daily routine, or teaching a learner to see the house as a system with inputs, flows, and outputs.
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。
Classical control and system dynamics for engineered systems — feedback and closed-loop control, transfer functions and block diagrams, poles/zeros and stability, time-domain response (rise time, overshoot, settling time), PID controllers and tuning, and frequency response (Bode plots, gain and phase margin). Traces feedback control from the flyball governor to modern controllers. Use when analyzing feedback loops, designing or tuning a PID controller, assessing stability from poles or margins, or characterizing transient response of a dynamic system.
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。
Statics, dynamics, stress-strain analysis, materials selection, failure modes, and finite element analysis concepts for engineered structures. Covers free-body diagrams, equilibrium, internal forces (shear and moment), beam deflection, column buckling, material properties, factor of safety, fatigue, fracture mechanics, and FEA workflow. Use when analyzing loads on structures, selecting materials, predicting failure, or interpreting structural behavior.
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。
Mathematical verification for physical calculations: unit tracking algebra (exponent maps), PhysicalQuantity pattern for compound units, SI/Imperial mixed-unit handling, Buckingham pi theorem for dimensionless groups, and common engineering dimensionless numbers. Activates for unit verification, dimensional consistency checks, scaling analysis, and calculation validation across all infrastructure domains.
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 simulation inputs across fidelity levels — OpenFOAM CFD cases, ngspice netlists, interactive React artifacts, and FreeCAD FEM setups — from verified engineering calculations.
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。
NASA Systems Engineering methodology mapped to cloud operations. Use when planning, executing, verifying, or documenting OpenStack cloud infrastructure following NASA SP-6105 and NPR 7123.1 processes. Provides phase gate criteria, document templates, and cross-references for all 7 SE lifecycle phases applied to cloud deployment and 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。
Generates complete construction documentation packages — BOM, installation sequences, commissioning checklists, and O&M manuals — from verified engineering designs.
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。
Brutally honest code review in the style of Linus Torvalds, focusing on data structures, simplicity, and pragmatism. Use when you want critical, no-nonsense feedback that prioritizes engineering fundamentals over style preferences.
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。
Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.
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 engineer CGX Cognionics Quick-20 EEG acquisition protocol using MCP RE tooling (Binary Ninja, Ghidra, radare2)
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 integrates **Boxxy sandbox boundary testing** with the complete Trail of Bits firmware extraction methodology. Use this for extracting and analyzing firmware in heavily obfuscated, containerized, or restricted environments.
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 initial binary triage by surveying memory layout, strings, imports/exports, and functions to quickly understand what a binary does and identify suspicious behavior. Use when first examining a binary, when user asks to triage/survey/analyze a program, or wants an overview before deeper reverse engineering.
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 validate-chunk reports errors or failures, when the user asks to "fix these errors", "resolve validation issues", "refine this chunk", or when specific build, lint, or type errors need surgical fixes. Makes precise, targeted edits to resolve specific validation issues without over-engineering.
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-engineer comprehensive specification documents from existing codebases through goal-driven reconnaissance, WBS-based parallel investigation, and iterative question-bank dialogue.
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。
Design, build, evaluate, or teach graph-based systems. Use for knowledge graphs, ontology/schema design, entity/relation/event extraction, entity resolution and fusion, GraphRAG or graph memory, and agent/task dependency graphs with concurrency, joins, failure handling, verification, or human gates.
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。
Specialist skill for Python data engineering — pandas, polars, DuckDB, numpy, ETL pipelines, tabular data ingestion, and notebook-to-module extraction. Use when working with dataframes, data validation at ingress boundaries, merge/join operations, typed column contracts, or choosing between pandas vs polars vs DuckDB for a data task.
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 implementing a Python feature, adding CLI commands, writing pytest suites, reviewing Python code, debugging, or refactoring. The primary Python engineering workflow orchestrator — classifies the task and delegates through this plugin's own specialist agents (architect → implement → test → review), sized to the task. Delegates to python-cli-architect (implementation), python-pytest-architect (tests), code-reviewer (review), python-cli-design-spec (architecture). Triggers on any Python task requiring specialist agent coordination or multi-agent 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。
Routes Python engineering tasks to specialist skills by matching trigger patterns before any architecture, plan, or code is written. Use when working with Typer CLI frameworks, Rich or Textual terminal UIs, CLI UI/UX design, questionary prompts, FastMCP/MCP servers, ty type checker, uv package manager, Hatchling build backend, TOML editing, pre-commit/prek hooks, async Python, PyPI packaging, complex linting, technical debt modernization, testing workflows, feature development, or stdlib-only scripting.
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 independently hunting Python code smells, deviations from engineering standards, maintenance hazards, or suspicious design choices in a bounded review surface.
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。
Works backward from the stated goal through its prerequisite chain — what must exist to reach the goal, then what each of those requires, back to the current state — classifying each prerequisite as AVAILABLE, DERIVABLE, or MISSING, and blocking planning until nothing is MISSING. Use before creating plans, delegating to agents, or defining acceptance criteria. Activates on specs, PRDs, tickets, RFCs, architecture designs, and multi-step engineering tasks. Always pass `#N` or an inline goal — invoking with no argument and no inline context returns BLOCKED. Integrates with CoVe-style planning 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。
Reviews Python boundaries, typing, error handling, tests, dependencies, and supported-version idioms against the target project's contracts and active tools. Loaded by dh:code-reviewer for Python source; uses Python-engineering standards when available and retains standalone checks otherwise.
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。
Design, create, update, and verify Vapi Squads and documented handoff tools through the public API. Use for choosing a single assistant versus a multi-assistant Squad, persistent or transient members, entry-member ordering, specialization boundaries, context engineering, variable extraction, model-specific handoff patterns, assistant-version pins, and safe Squad updates.
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 reviewing a skillsaw PR. Dispatches 7 specialist reviewers (Architecture, Python Expert, Security & Supply Chain, QA Engineer, Technical Writer, Ecosystem, Slopinator) as parallel sub-agents by default, then synthesizes a single verdict. Use --serial for cheaper inline 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。