「understand」の検索結果

Understanding this is key to prompt engineering: you

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 any GitHub repository in AI-friendly format. Convert entire repos to single markdown documents, generate architecture diagrams with Mermaid, inspect structure trees, language breakdowns, and recent activity. Includes GitHub URL tricks, API shortcuts, and advanced search techniques. Read-only analysis — never executes code from repositories. Built for AI agents — Python stdlib only, no dependencies. Use for repository analysis, code architecture review, open source research, GitHub intelligence, repo documentation, and codebase understanding.

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。

Personal knowledge base powered by Ensue for capturing and retrieving understanding. Use when user wants to save knowledge, recall what they know, manage their toolbox, or build on past learnings. Triggers on "save this", "remember", "what do I know about", "add to toolbox", "my notes on", "store this concept".

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。

Tell the agent to zoom out and give broader context or a higher-level perspective. Use when you're unfamiliar with a section of code or need to understand how it fits into the bigger picture.

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 organize files across your computer by understanding context, detecting duplicates, suggesting folder structures, and automating cleanup. Maintain a clean digital workspace 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。

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。

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。

Extract and analyze competitor ads from ad libraries (Facebook, LinkedIn, etc.) to understand messaging strategies, pain points highlighted, and creative approaches that resonate with audiences.

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。

Language models exhibit predictable degradation patterns as context length increases. Understanding these patterns is essential for diagnosing failures and designing resilient systems.

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。

Refactor code units whose size or mixed responsibilities impede understanding, testing, or change. Use when recent work makes a function, class, or module materially harder to reason about.

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。

Relentlessly interview the user about THEIR plan, one question at a time, until shared understanding. Checkpoints answers so progress survives a reset. Do NOT use to propose solutions.

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。

DraftForge test infrastructure for writing backend unit tests, Playwright E2E tests, and managing test data population. This skill should be used when writing new tests, adding test fixtures, creating populate functions for new features, adding Playwright E2E specs, using login/auth fixtures, creating test users/orgs/leagues/tournaments, or understanding the test data architecture. Covers backend Django tests via Docker, Playwright config (projects, workers, sharding), test auth endpoints that expose backend login to frontend, and feature-isolated test data patterns.

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。

Inspect an explicit Fusion design, parameters, geometry, references, configuration and health without editing it. Use for model understanding or engineering audits.

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。

Setup subskill for simmer. Inspects the artifact or workspace, infers evaluation contracts and search space, proposes a complete assessment to the user, and produces a setup brief after confirmation. Conversational, not form-based — the agent does the work of understanding the problem, then presents what it found. Do not invoke directly — called by simmer orchestrator.

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 user says "simmer this", "refine this", "hone this", "iterate on this", or asks to improve a specific artifact over multiple rounds. Runs an iterative refinement loop with investigation-first judges that read the code, understand the problem, and propose evidence-based improvements. Auto-selects single judge or multi-judge board based on complexity. Works on any artifact type: documents, prompts, specs, emails, creative writing, API designs, pipelines, codebases. Supports multi-file workspace targets, runnable evaluators, and open-ended optimization (model selection, pipeline topology, prompt tuning).

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 the user asks to "create a plugin", "scaffold a plugin", "understand plugin structure", "organize plugin components", "set up plugin.json", "use ${CLAUDE_PLUGIN_ROOT}", "add commands/agents/skills/hooks", "configure auto-discovery", or needs guidance on plugin directory layout, manifest configuration, component organization, file naming conventions, or Claude Code plugin architecture best practices.

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。

Compassionate bereavement support, memorial creation, grief education, and healing journey guidance. Specializes in understanding grief stages, creating meaningful tributes, and supporting the non-linear path of loss.

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 visualizing and explaining braid theory, knot mathematics, and topological concepts for educational purposes. Use for creating interactive visualizations, explainer cards, step-wise animations, and translating abstract algebra into intuitive understanding. Activate on keywords: braid theory, knot visualization, σ notation, crossing diagrams, Yang-Baxter, topological education. NOT for general math tutoring, pure knot invariant computation, or non-educational knot theory research.

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。

Cross-cultural communication frameworks for understanding discourse patterns across cultures

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 temporal event detection, spatio-temporal clustering (ST-DBSCAN), and photo context understanding. Use for detecting photo events, clustering by time/location, shareability prediction, place recognition, event significance scoring, and life event detection. Activate on 'event detection', 'temporal clustering', 'ST-DBSCAN', 'spatio-temporal', 'shareability prediction', 'place recognition', 'life events', 'photo events', 'temporal diversity'. NOT for individual photo aesthetic quality (use photo-composition-critic), color palette analysis (use color-theory-palette-harmony-expert), face recognition implementation (use photo-content-recognition-curation-expert), or basic EXIF timestamp extraction.

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。

Master of text-based visual communication using ASCII art, Unicode box-drawing, and structured diagram notation. Creates clear, maintainable diagrams for systems, processes, hierarchies, relationships, and psychological structures. Proactively generates diagrams to enhance understanding. Activate on visualization needs, system architecture, process flows, psychological mapping, or when complex concepts would benefit from visual representation. NOT for photo editing, vector graphics, or GUI-based design tools.

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。

Normalize read-depth copy-ratio profiles and segment them into copy-number regions using circular binary segmentation (CBS, DNAcopy), hidden Markov models, HaarSeg, and fused-lasso methods. Covers GC-content, mappability, and replication-timing (wave-artifact) bias correction, panel-of-normals/PCA denoising, diploid-baseline centering, and algorithm selection by sequencing depth and event size. Use when choosing a segmentation algorithm, correcting depth bias, diagnosing oversegmentation or a mis-centered baseline, tuning CBS or HMM parameters, or understanding why a downstream CNV caller produced fragmented or shifted segments.

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。