955 件 ・ 関連度順
概要と使いどころ
Enable, disable, or inspect Session Cartographer Turbo Mode, the optional shared warm recall backend for Claude Code and Codex. Use when the user asks about Turbo Mode, faster recall, or the global recall backend.
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。
Open the Session Cartographer Explorer web UI for visual browsing of Claude Code and Codex session history.
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。
Render the beat table into alpha overlays. Use at the graphics stage after gate 3, or when the user says "build the graphics" or "render the overlays".
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 tsift for token-efficient repository navigation, code search and reading, call graphs, diffs, logs, tests, session context, and workspace memory. TRIGGER: exploring or changing a codebase with tsift installed, or working on the tsift repo. SKIP: plain file-level glob, non-code web search. VERSION CHECK: compare `tsift --version` against tsift-version below before trusting any command text copied from this file.
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 git repositories to build a security ownership topology (people-to-file), compute bus factor and sensitive-code ownership, and export CSV/JSON for graph databases and visualization. Trigger only when the user explicitly wants a security-oriented ownership or bus-factor analysis grounded in git history (for example: orphaned sensitive code, security maintainers, CODEOWNERS reality checks for risk, sensitive hotspots, or ownership clusters). Do not trigger for general maintainer lists or non-security ownership questions.
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 Cody (Sourcegraph Cody, code search, AI autocomplete, context awareness)
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 en algorithmes (Big-O, dynamic programming, graphs, sorting, LeetCode 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。
Generate archetype-driven semantic design tokens (colors, typography, spacing, radius, motion, elevation) that don't look vibecoded. Hard-bans Tailwind-default palettes, Inter-only typography, and purple→pink gradients unless the chosen archetype explicitly demands them. Load when the user asks to generate design tokens, create a design system, set up CSS custom properties, build a token scale, design a color system, set up typography scale, or when frontend-design routes here during token generation. Also triggers on "design tokens for", "token system", "CSS variables for design", "set up a theme", "build a design system foundation". Sub-skill of frontend-design. Always reads ARCHETYPE.md first.
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。
Build or update the code review knowledge graph. Run this first to initialize, or let hooks keep it updated automatically.
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。
Index a codebase with GitNexus and serve an interactive knowledge graph via web UI + Cloudflare tunnel.
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 REST/GraphQL APIs: status codes, auth, schemas, repro.
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 modern GraphQL with federation, performance optimization, and enterprise security. Build scalable schemas, implement advanced caching, and design real-time systems. Use PROACTIVELY for GraphQL architecture or performance optimization.
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。
大きな機能開発や移行の目標を、複数回の作業に分けた実行計画にします。各工程の背景、依存関係、検証方法をまとめ、別のエージェントへの引き継ぎを支えます。
Use when you need to ask questions about a codebase or understand code using a knowledge graph
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 business domain knowledge from a codebase and generate an interactive domain flow graph. Works standalone (lightweight scan) or derives from an existing /understand knowledge graph.
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。
Cluster code by graph community detection via npx ruvector@0.2.25 hooks graph-cluster (spectral / Louvain)
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。
Build a graph-structured dossier on a seed entity via parallel fan-out + recursive expansion across web, memory, knowledge-graph, codebase, ADR index, and git intel
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。
Builds and troubleshoots TorchDrug 0.2.1 workflows for molecular graphs, property prediction, self-supervised pretraining, molecule generation, retrosynthesis, protein representation learning, and knowledge graph reasoning. Use when code imports torchdrug or needs its datasets, models, tasks, or Engine.
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。
GPU-accelerates scientific Python on NVIDIA hardware and verifies that the result is correct and faster. Use for CUDA/GPU optimization; CPU-bound NumPy, SciPy, pandas, scikit-learn, NetworkX, scikit-image, vector-search, image-processing, graph, simulation, or file-I/O workloads; CuPy, cuDF, cuML, cuGraph, cuVS, cuCIM, KvikIO, Warp, Newton, Numba-CUDA, or RAFT questions; and profiling, memory-transfer, kernel, or multi-GPU bottlenecks. Also use when large data-parallel Python code is slow and GPU acceleration is a plausible option, even if the user does not name CUDA.
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 you need a deep, implementation-ready engineering plan for a code change — built from GitNexus graph intelligence, statement-level PDG analysis, and targeted source verification, compact enough that an implementation agent can start without re-investigating. Also strengthens existing plans via Deepen mode. Examples: "/gitnexus-plan Add retry support to the ingestion pipeline", "/gitnexus-plan deepen docs/plans/<plan>.md", "plan this change using the knowledge graph".
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 creating, editing, or generating draw.io diagram files (.drawio, .drawio.svg, .drawio.png). Covers mxGraph XML authoring, shape libraries, style strings, flowcharts, system architecture, sequence diagrams, ER diagrams, UML class diagrams, network topology, layout strategy, the hediet.vscode-drawio VS Code extension, and the full agent workflow from request to a ready-to-open file.
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。
Deterministic orchestration graph runtime - declarative DAG pipelines with journal-based crash recovery
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。
Compile documents, notes, web content, transcripts, research materials, or code repositories into an evidence-grounded, visualization-ready knowledge graph with semantically typed entity nodes, statement-level provenance, and typed relationship edges. Use with ov compile to create or incrementally refresh `entities/*.md` node artifacts and a root `relations.jsonl` edge file for people, organizations, groups, animals, places, products, projects, systems, services, modules, datasets, standards, documents, events, and other identifiable things.
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。
Build a two-tier PKI Certificate Authority hierarchy (offline Root CA plus issuing Intermediate CA) using OpenSSL and the Python cryptography library, covering certificate extensions, CRL distribution points, OCSP responder configuration, and certificate policy management. Use when standing up an internal CA, issuing or revoking X.509 certificates, or designing PKI trust hierarchies for TLS, code-signing, or client-authentication use cases.
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。