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概要と使いどころ
Carbon allotropes and nanoscale materials — graphite, diamond, fullerenes (C60 and family), carbon nanotubes, graphene, and the broader class of low-dimensional materials. Covers synthesis routes (arc discharge, laser ablation, CVD, exfoliation), structural characterization, exceptional mechanical and electronic properties, and the gap between laboratory demonstrations and structural-scale applications.
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Schools of historical thought, methodology debates, and the philosophy of history. Covers the major historiographical traditions (Annales, Marxist, feminist, postcolonial, subaltern, world-systems), their methodological commitments, their contributions and limitations, and the enduring debates about objectivity, narrative, and the nature of historical knowledge. Use when evaluating how different historians approach the same subject, understanding why historical interpretations change over time, or assessing the theoretical framework underlying a historical argument.
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Earth systems science covering plate tectonics, landforms, erosion, biomes, hydrosphere, atmospheric circulation, and the interactions among lithosphere, hydrosphere, atmosphere, and biosphere. Provides frameworks for analyzing how physical processes shape landscapes over geological and human timescales. Use when reasoning about landforms, natural hazards, climate patterns, ocean currents, biogeography, or any question about how Earth's physical systems operate and interact.
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Spatial dimensions of political power, state sovereignty, territorial conflict, borders, international governance, and critical geopolitics. Covers classical geopolitics (Mackinder, Ratzel, Mahan), critical geopolitics (Said, O Tuathail), state territory and sovereignty, border theory, international organizations and governance, electoral geography, and postcolonial perspectives on power and space. Use when reasoning about territorial disputes, borders, international relations, state power, colonialism and its legacies, or the politics of geographic representation.
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Grammar of graphics, chart type selection, color theory, interactive visualization, dashboards, and the principles of honest, effective data display. Covers Tufte's data-ink ratio, Bertin's visual variables, perceptual principles, accessibility, small multiples, annotation, and the full workflow from exploratory plots to publication-quality graphics. Use when creating charts, designing dashboards, critiquing visualizations, or choosing how to display data.
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Before dispatching a multi-agent team, run a spectral diagnostic on the proposed communication graph and emit a (ρ, Δ, κ) coordination signature plus a pass/fail verdict against per-task-class thresholds. Builds the row-stochastic operator P from the team graph, computes the successor representation M = (I − γP)⁻¹, and ranks the topology for robustness (κ, condition number), consensus (Δ, spectral gap), and drift (ρ, spectral radius). Per Parks & Alharthi (arxiv 2605.11453), rank order on (κ, Δ, ρ) predicts coordination quality pre-execution with rank correlations of 1.0 / 0.5 / −1.0. Triggers: "dispatch the team", "team topology check", "before running the agents", "is this team configuration OK", "team pre-flight".
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。
Stanford FDCI research bridge connecting Dan Boneh's cryptographic primitives (ZK proofs, BLS signatures, threshold cryptography) with Tim Roughgarden's mechanism design (TFM, MEV mitigation, welfare maximization).
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Use for architecture review, dependency graphs, coupling analysis, or circular dependency detection. Establishes project module namespaces and traces imports plus Claude plugin hook, skill, script, PEP 723, and MCP boundaries. Emits partitioned Mermaid graphs with cycle, coupling, and ownership signals; verifies contract and consequence before assigning severity. Registers diagrams as codebase-analysis artifacts.
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Comprehensive AI/ML development guide for LangChain, LangGraph, and ML model integration in FastAPI. Use when building LLM applications, agents, RAG systems, sentiment analysis, aspect-based analysis, chain orchestration, prompt engineering, vector stores, embeddings, or integrating ML models with FastAPI endpoints. Covers LangChain patterns, LangGraph state machines, model deployment, API integration, streaming, error handling, and best practices.
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Compose polished charts (timeseries, bar, line, area, pie, scatter, or anything else the data calls for) from tabular data using the chartkit primitives, producing PNG, SVG, or self-contained interactive HTML. Use when the user asks to chart, graph, plot, or visualize data and wants something better than raw matplotlib defaults.
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Design system that makes HTML output look like a professional consulting deliverable instead of default AI styling. Use WHENEVER generating any HTML document — report, analysis memo, proposal, research summary, dashboard, artifact — and when the user says 「HTMLで資料」「HTMLでまとめて」「レポートにして」「コンサル風に」「資料っぽく」「デザインがダサい」 or asks to restyle existing AI-generated HTML. Replaces boxes, borders, gradients, emoji and rainbow colors with whitespace-driven, typography-first, print-ready (A4) design.
Unified code intelligence — Skeleton Index (zero-dep, <4s) + AST knowledge graph (CodeGraph) + architecture diagrams (Mermaid) + smart context builder. Pre-indexes code structure so AI agents understand any codebase instantly. 95% token compression for onboarding. 30% fewer tokens for deep analysis.
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Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.
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Give LangGraph agents memory management and search tools so they can store, retrieve, and update durable facts across sessions.
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Use at the start of any session on a project with a build graph (`.hedgehog/hedgehog.db`), and again at every claim/dispatch/verify cycle within it. Owns consuming the build graph — claiming task packets, delegating each to the layer's agent, running `hedgehog verify` to gate the commit, recording debt and decisions, the intent check at an intent's last layer, and when to clear context. Not for a build agent handed an already-claimed packet — that agent never claims, dispatches, or verifies; this skill is the orchestrating session's own.
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。
GraphQL expert including schema design, Apollo Client/Server, and caching
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。
API security testing and validation for REST/GraphQL/gRPC endpoints, contract testing, load testing, fuzzing, and Postman/Bruno/Hurl workflows
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Improve UI typography by fixing font choices, type scale, hierarchy, weight, and readability so text feels intentional. Use when the user mentions fonts, typography, type scale, readability, text hierarchy, or sizing that feels off.
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 and edit high-quality images using Google's Nano Banana Pro (Gemini 3 Pro Image) AI model. Use this skill when working with AI image generation or editing tasks including (1) Creating images from text prompts with professional quality, (2) Editing existing images with natural language instructions, (3) Multi-turn iterative image refinement, (4) Product photography and marketing visuals, (5) Creating infographics and diagrams with text, (6) Photorealistic and artistic image generation, (7) Batch image generation workflows, (8) Testing and troubleshooting Gemini image generation API. Supports up to 4K resolution, multiple aspect ratios, reference images, and advanced prompting techniques for cinema-quality results.
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Analyze a repository's type system and generate type-safe DAG execution pipelines with GraphSentry-style certificate verification. This skill should be used when building LLM-driven workflows that need deterministic type safety, when composing typed operations into validated execution graphs, or when adding contract-checked pipeline orchestration to any codebase. Supports Python (Pydantic) and TypeScript (Zod).
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。
Convert a semantic core into crawlable SEO and LLM-friendly information architecture. Use this skill when the user asks for URL structure, page taxonomy, canonical rules, hreflang groups, page roles, pillar/topic/news/article/blog/project separation, multilingual route strategy, or a durable content model such as one short brief plus one longform article. It prevents duplicate public content bodies and hands link-graph work to internal-link-graph-architect.
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。
Queries the NCATS Translator ARAX production API for bounded, typed, provenance-rich one-hop and endpoint-pinned two-hop biomedical knowledge-graph relationships. Use for Biolink-constrained RTX-KG2 lookup, explicit selected-provider ARAX federation, separate entity normalization, qualifier-aware graph traversal, and inspection of TRAPI edge bindings, publications, and knowledge-source provenance. Do not use for inference, ranking, open-ended pathfinding, clinical guidance, or sensitive queries.
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。
Drive a GitHub Copilot (or any bot reviewer) pull-request review to a clean pass without babysitting it: fix each finding in its own commit, reply to the review thread with the fix sha, resolve the thread, re-request the bot, and poll for the async re-review. Covers the thread node-id (PRRT_...) vs comment databaseId distinction, the resolveReviewThread GraphQL mutation, the copilot-pull-request-reviewer[bot] slug, and how to read the bot's verdict (COMMENTED plus a "human review recommended" banner is not a blocking finding). Use when Copilot has left review comments on your PR, when bot review threads must be closed out with an auditable fix-reply-resolve trail before merge, or when you need to verify that a re-review actually landed on the new HEAD rather than the old one.
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。
Review web design for layout quality, typography, colour usage, spacing, responsive behaviour, brand consistency, and visual hierarchy. Covers design principles evaluation and improvement recommendations. Use when reviewing a design mockup before development, assessing an implemented site for design quality, providing feedback during a design review session, evaluating brand consistency, or checking responsive behaviour across breakpoints.
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。