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概要と使いどころ
Interactive pixel-art command center dashboard. Visual business HQ with instant hotkey navigation to all ops commands, live status indicators, fire alerts, C-suite reports, settings, sharing, and FAQ.
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。
AI-powered browser automation — navigate sites, fill forms, extract structured data, log in with stored credentials, and build reusable multi-step workflows using natural language. Install: pip install skyvern && skyvern setup
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。
Automate Confluence page creation, content search, space management, labels, and hierarchy navigation via Rube MCP (Composio). Always search tools first for current schemas.
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。
Official NVIDIA-authored guidance for navigating PhysicsNeMo — pick the model, datapipe, or example for a SciML/AI4Science task (surrogates, forecasting, downscaling, physics-informed, inverse, generative). Points at existing files via live repo search; never writes code. Do NOT use for installation or environment setup, training-loop or other code authoring/scaffolding, contributor/CI/packaging questions, repo-specific questions in physicsnemo-sym/-cfd/-curator, or general (non-physics) ML/PyTorch.
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。
Investigate a failing GitHub Actions run or job and create a GitHub issue for the failure.
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 this skill for OpenFold3, NVIDIA's BioNeMo NIM microservice for biomolecular structure prediction. Invoke whenever the user mentions OpenFold3 or needs protein, protein-ligand, protein-DNA/RNA, or multi-chain complex prediction with the hosted NVIDIA API or local Docker NIM. Covers endpoint choice, auth, request payloads, output artifacts, confidence scores, and local container setup.
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。
Execute one scoped implementation or investigation item and return evidence without changing workflow authority.
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。
Research a topic and grow your knowledge graph. Uses Exa deep researcher, web search, or basic search to investigate topics, files results with full provenance, and chains to processing pipeline. Triggers on "/learn", "/learn [topic]", "research this", "find out 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。
Golang benchmarking, profiling, and performance measurement. Use when writing, running, or comparing Go benchmarks, profiling hot paths with pprof, interpreting CPU/memory/trace profiles, analyzing results with benchstat, setting up CI benchmark regression detection, or investigating production performance with Prometheus runtime metrics. Also use when the developer needs deep analysis on a specific performance indicator - this skill provides the measurement methodology, while `samber/cc-skills-golang@golang-performance` provides the optimization 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。
Golang semantic code intelligence via `gopls`, the official Go language server — go-to-definition, find references, call/implementation hierarchy, workspace symbol search, package API discovery, diagnostics, safe rename, refactors (extract/inline/fill/rewrite code actions), formatting, and generated tests. Reaches an agent via gopls's own MCP server (`go_*` tools), Claude Code's native `LSP` tool, or the `gopls` CLI. Use when navigating or refactoring Go code — jumping to a definition, finding call sites before a rename, understanding a file's or package's dependencies, running diagnostics after an edit, or extracting/inlining/renaming. Not for the published ecosystem — packages not in your `go.mod`, versions, licenses, importers — → See `samber/cc-skills-golang@golang-pkg-go-dev` skill (`godig`). Not for a whole-tree vulnerability audit → See `samber/cc-skills-golang@golang-security` skill (`govulncheck`).
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。
Golang everyday observability — the always-on signals in production. Covers structured logging with slog, Prometheus metrics, OpenTelemetry distributed tracing, continuous profiling with pprof/Pyroscope, server-side RUM event tracking, alerting, and Grafana dashboards. Apply when instrumenting Go services for production monitoring, setting up metrics or alerting, adding OpenTelemetry tracing, correlating logs with traces, migrating legacy loggers (zap/logrus/zerolog) to slog, adding observability to new features, or implementing GDPR/CCPA-compliant tracking with Customer Data Platforms (CDP). Not for temporary deep-dive performance investigation (→ See `samber/cc-skills-golang@golang-benchmark` and `samber/cc-skills-golang@golang-performance` skills).
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。
[omh] Software slowness, memory leaks, or cost spikes: find where a system is actually slow, leaking, or expensive across runtime, memory, token cost, storage, rendering, inference, CI, and query domains, then fix one measured hot path at a time behind a regression budget. Use when the user says: ultraperf, ulw-perf, performance audit, performance bottleneck, find the bottleneck, profile the hot path, memory leak investigation, token cost hotspot.
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。
[omh] Production is down or an incident is open: command an incident that is still open -- severity as declared live state, commander and roles, an append-only timeline, a recorded temporary mitigation, verified recovery, and the customer notice. Use when the user says: live-incident-response, live incident response, incident response, active incident, ongoing incident, open incident, incident open, incident commander.
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。
Query and search the EMBL-EBI Ontology Lookup Service (OLS) for biomedical ontology terms, definitions, and hierarchies across 250+ ontologies (e.g., GO, DOID, HP). Use when the user asks to search for terms, retrieve details, navigate hierarchies (parents, children, ancestors), look up properties and individuals, get autocomplete suggestions, or access ontology metadata and statistics.
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 want to search for or download experimentally-determined 3D structures for biomolecules (proteins, nucleic acids, bound ligands). Supports searching by sequence similarity, structure similarity, chemical and other attributes. Also use to get metadata about biomolecular structure experiments.
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。
Visualize, analyze, and render protein and molecular structures using PyMOL. Use when the user wants to create images of protein structures, perform structural alignments or superposition, measure distances or contacts, highlight binding sites or active site residues, color by B-factor/pLDDT, or analyze protein-ligand interactions. Do not use for docking, molecular dynamics, or sequence-only analysis.
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 says "check Datadog", "查 Datadog", "查日志", "check logs", "crash logs", "查 crash", "gateway crash", "查告警", "check alerts", "check metrics", or needs to investigate production issues via Datadog Logs API.
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。
App dashboard with purple-themed aesthetic, top-bar navigation, card-based layouts, and developer-first workflows.
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。
Enter explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements. Use when the user wants to think through something before or during a change.
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。
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
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。
Analytical thinking patterns for comprehensive evaluation, code audits, security analysis, and performance reviews. Provides structured templates for thorough investigation with extended thinking support.
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。
Answers questions about a code repository using source file analysis. Use when the user asks a question about how something works, wants to understand a component, or needs help navigating 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。
Configure Azure API Management as an AI Gateway for AI models, MCP tools, and agents. WHEN: semantic caching, token limit, content safety, load balancing, AI model governance, MCP rate limiting, jailbreak detection, add Azure OpenAI backend, add AI Foundry model, test AI gateway, LLM policies, configure AI backend, token metrics, AI cost control, convert API to MCP, import OpenAPI to gateway.
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。
Conducts multi-turn iterative deep research on specific topics within a codebase with zero tolerance for shallow analysis. Use when the user wants an in-depth investigation, needs to understand how something works across multiple files, or asks for comprehensive analysis of a specific system or pattern.
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。