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概要と使いどころ
Classify XQUIC GitHub issues with an evidence-backed L1-L4 resolution-complexity label while keeping validity, priority, severity, and disposition separate and skipping uniquely labeled issues unless the user explicitly forces a recheck. Use when triaging one issue or a batch of issues, creating an issue-complexity backlog, or applying or correcting L1-L4 GitHub labels.
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 PR(s) using comprehensive review guidelines including security, correctness, clean code, TypeScript, React patterns, i18n/RTL, performance, and accessibility. Use when reviewing pull requests or code 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。
Findings-first code review workflow for AI coding agents. Use when the user asks to review uncommitted changes, commits in a date range, or a branch compared to the main branch / PR-style diff. Focuses on bugs, regressions, correctness risks, missing tests, security/data-safety issues, and other behavior-changing defects.
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。
Automated Planning utilities for loading PDDL domains and problems, generating plans using classical planners, validating plans, and saving plan outputs. Supports standard PDDL parsing, plan synthesis, and correctness 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。
Quantum mechanics simulations and analysis using QuTiP (Quantum Toolbox in Python). Use when working with quantum systems including: (1) quantum states (kets, bras, density matrices), (2) quantum operators and gates, (3) time evolution and dynamics (Schrödinger, master equations, Monte Carlo), (4) open quantum systems with dissipation, (5) quantum measurements and entanglement, (6) visualization (Bloch sphere, Wigner functions), (7) steady states and correlation functions, or (8) advanced methods (Floquet theory, HEOM, stochastic solvers). Handles both closed and open quantum systems across various domains including quantum optics, quantum computing, and condensed matter physics.
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 considered when you need to normalize testing engineers' written defect reasons following the provided product codebooks. This skill will correct the typos, misused abbreviations, ambiguous descriptions, mixed Chinese-English text or misleading text and provide explanations. This skill will do segmentation, semantic matching, confidence calibration and station validation.
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 Lean 4 (.lean files), writing mathematical proofs, seeing "failed to synthesize instance" errors, managing sorry/axiom elimination, or searching mathlib for lemmas - provides build-first workflow, haveI/letI patterns, compiler-guided repair, and LSP integration
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。
Reduce dimensionality of multivariate data using PCA with varimax rotation. Use when you have many correlated variables and need to identify underlying factors or reduce collinearity.
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。
Tools and techniques for detrending time series data in macroeconomic analysis. Use when working with economic time series that need to be decomposed into trend and cyclical components. Covers HP filter, log transformations for growth series, and correlation analysis of business cycles.
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 comprehensive test cases including edge cases, stress tests, and counter-examples for algorithm correctness verification. Supports random generation, constraint-based generation, and brute force oracle comparison.
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 and verify loop invariants for correctness 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。
Assist in constructing algorithm correctness 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。
Compare multiple solutions for correctness and 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。
Scaffolds MCP App project structure with correct directory layout, dependencies, entry points, and framework-specific templates. Handles React (useApp hook), Vanilla JS, Vue, Svelte, Preact, and Solid.
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。
Autonomously engage with complex coding tasks — multi-step planning, tool use, self-correction, and solution verification without human intervention.
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-dimensional code review across correctness, security, performance, and maintainability with confidence-gated reporting and remediation loops.
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。
Root cause analysis frameworks including log-first investigation, git bisect correlation, and pattern-based diagnosis with confidence scoring.
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 asks to review, verify, or audit a report, manuscript, or analysis in the workspace for traceability — resolving citations, flagging numbers with no source, and checking figures against the code that generated them. Emits a structured review block the app renders as reviewer findings. Verifies traceability, never "correctness".
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 errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source of invalid data or incorrect 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。
Combine static analysis with model-assisted code review to assess security, performance, correctness, and architecture. Use when designing review automation or reviewing complex 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。
Search logs and codebases for error patterns, stack traces, and anomalies. Correlates errors across systems and identifies root causes. Use PROACTIVELY when debugging issues, analyzing logs, or investigating production errors.
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 Conductor project artifacts for completeness, consistency, and correctness. Use after setup, when diagnosing issues, or before implementation to verify project 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。
Combine static analysis with model-assisted code review to assess security, performance, correctness, and architecture. Use when designing review automation or reviewing complex 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。
Draft and review contributions to existing MEX project knowledge. Use when the user asks to capture a discussion or decision in project knowledge, propose an addition or correction for team review, or explicitly invokes /mex-inbox or $mex-inbox. Also supports existing Spec proposals. Do not activate for brainstorming alone, routine GROW upkeep, email inboxes, session logs, or handoffs.
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。