「chi」の検索結果

Structures git workflow practices. Use when making any code change. Use when committing, branching, resolving conflicts, or when you need to organize work across multiple parallel streams.

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 *.excalidraw or *.excalidraw.json files, user mentions diagrams/flowcharts, or requests architecture visualization - delegates all Excalidraw operations to subagents to prevent context exhaustion from verbose JSON (single files: 4k-22k tokens, can exceed read limits)

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。

Debug LangChain and LangGraph agents by fetching execution traces from LangSmith. Analyze agent behavior, investigate errors, and review tool calls and performance metrics.

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。

Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".

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。

Triage GitHub issues through a label-based state machine. Use when user wants to create an issue, triage issues, review incoming bugs or feature requests, prepare issues for an AFK agent, or manage issue 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。

Create and evolve design systems with design tokens, component architecture, accessibility guidelines, and documentation templates. Ensures consistent, scalable, and accessible UI across products.

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。

Context optimization extends the effective capacity of limited context windows through strategic compression, masking, caching, and partitioning. The goal is not to magically increase context windows but to make better use of available capacity.

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。

Datadog CLI for searching logs, querying metrics, tracing requests, and managing dashboards. Use this when debugging production issues or working with Datadog observability.

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。

Records decisions and documentation. Use when making architectural decisions, changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.

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。

Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.

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。

6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.

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。

Validate Azure deployments against functional, security, performance, and operational criteria before production release. Use this skill when users ask for readiness checks, health verification, or production sign-off gates. Covers Well-Architected Framework validation, SLA verification, and release readiness.

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。

A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

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。

Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration.

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。

Map Azure architectures and operations to security and compliance controls. Use this skill when users ask for governance, policy enforcement, audit readiness, or regulatory alignment. Covers ISO, SOC2, HIPAA, PCI-DSS, and custom compliance frameworks.

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。

Implement dependency injection in Angular v20+ using inject(), injection tokens, and provider configuration. Use for service architecture, providing dependencies at different levels, creating injectable tokens, and managing singleton vs scoped services. Triggers on service creation, configuring providers, using injection tokens, or understanding DI hierarchy.

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 and apply Azure role-based access control with least privilege at the right scope. Use this skill when users ask about permissions, role assignments, access errors, or governance. Covers built-in roles, custom roles, managed identities, PIM, and access reviews per Well-Architected 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。

Train an ML model in the QuantConnect ML-Training-Pipeline with thermal-safe GPU usage and rigorous validation. Arguments: <architecture|script> [--dry-run] [--seeds 0,1,7,42,99] [--folds 5] [--bg]

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。

Pedagogical patterns for enriching notebooks (GameTheory model). Use when adding interpretations, structuring notebooks, or creating educational content in Jupyter notebooks.

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。

Safely auto-detect the current machine's hardware (GPU, VRAM, system RAM, OS) with read-only commands, then recommend the top 3 local AI models to run — most powerful that fits, best for coding, and best small-and-fast — each with download links. Use when someone asks "what AI models can my computer run" or "what's the best local model for my rig".

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。

Shape reusable library APIs for Compose modules. Design public composables, split sample-app code from reusable library code, review naming and extensibility.

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。

Interactive logo & brand design strategist. Runs a strategy workshop, narrows a creative direction, lands a single centralized concept, then outputs a condensed branding table plus 10+ logo ideas with rationale. Use when the user wants to design a logo, develop a brand identity, write a logo brief, brainstorm logo concepts, or run brand strategy before sketching. Triggers include "design a logo", "logo ideas", "brand identity", "help me with my logo", "logo brief", "what should my logo be".

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。

Spin up a coordinated multi-agent swarm (hierarchical or mesh topology) to work a complex, multi-file task on a ruOS desktop. Use when a task needs 3+ agents working in parallel with anti-drift coordination; skip for single-file edits.

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。

Decompile a function to C-like pseudocode for human-readable analysis. Use to understand function logic, review control flow, or prepare for code pattern matching.

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。