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概要と使いどころ
Dasel v3 selectors for Spring bean factory XML — use when querying any Spring ApplicationContext XML for bean discovery, dependency wiring, JMS destination mapping, property injection extraction, or cross-bean reference tracing. Load this skill before writing dasel selectors against Spring bean XML files (applicationContext.xml, *_beans.xml, spring-*.xml).
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Use when a validated ChatGPT/Codex Plugin needs accurate Plugin Directory fields, discovery metadata, starter prompts, and reviewer-facing listing details grounded in the packaged product.
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 validating name-directory matching
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Delete one or more vectors by key. Requires authentication. Use for Agentuity cloud platform operations
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。
Get a specific vector entry by key. Requires authentication. Use for Agentuity cloud platform operations
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。
Get statistics for vector storage. Requires authentication. Use for Agentuity cloud platform operations
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。
List all vector namespaces. Requires authentication. Use for Agentuity cloud platform operations
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。
Search for vectors using semantic similarity. Requires authentication. Use for Agentuity cloud platform operations
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。
AgentDB Vector Search Optimization operates on 3 fundamental 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。
Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
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。
Advanced AgentDB Vector Search Implementation operates on 3 fundamental 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。
Set up Claude Tag for oncall for a team, from that team's standing (public) oncall / monitoring channel. Two things: it sets the channel up for monitoring, so alerts and incident posts here (from a person or another Slack bot) get triaged and acted on automatically, and it finds and sets up the connectors, plugins and skills Claude uses for oncall. A workspace can have several such channels; run once in each, by anyone, and every run adds or updates that team's section in the one oncall memory in shared workspace memory. Use on "set up oncall", "init oncall", "configure Claude for on-call". Surveys the agent connectors an admin configured for Claude, proves one with a read-only pull so access is verified, explores tools, Slack, repos and docs to learn how oncall works here, then recommends what's missing and walks the team through setup. The result goes into the indexed oncall memory every channel reuses; the other skills (incident init, investigation, handoff) pick it up 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。
Medical/scientific paper writing workflow skill. Manages the full pipeline from literature search to submission-ready manuscript. Creates and manages a project directory with IMRAD-format section files, literature matrix, reference management, and quality checklists. Supports both English and Japanese papers. Triggers: 'write paper', 'paper-write', 'start manuscript', '論文を書く', '論文執筆', '論文プロジェクト', 'manuscript', 'research paper', '原稿作成'.
Evaluate an open source project's AGENTS.md and produce a corpus entry for the /agents-md directory. Use when adding a project to the directory, refreshing an existing entry, or running a batch of candidate repositories.
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。
Fetches tweets from Twitter List, scores them using data metrics and AI analysis, and generates topic recommendation reports for content creators.
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Uses AWS CloudWatch SDK (boto3) to configure anomaly detection bands on metrics via PutAnomalyDetector API. Integrates with SNS for notifications and CloudWatch Synthetics for canary-based uptime monitoring.
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Generates Airbyte source and destination connector configurations using the Airbyte API /v1/sources/create and /v1/destinations/create endpoints. Validates connection specs against the Airbyte Protocol.
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。
Airbyte is the leading open-source data integration platform providing 600+ pre-built connectors for ELT pipelines from APIs, databases, and files to data warehouses, lakes, and lakehouses. It supports both self-hosted and cloud deployments with a no-code connector builder.
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。
Verification methodology and gate checklist for the tdmcp Connectors Directory submission — run the docs build, build and inspect the .mcpb bundle, sweep for stale .dxt references, and cross-check the form-answer draft against the real requirements. Use to validate the submission package before a human submits, by executing commands and quoting evidence, not by trusting that work was done.
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。
Operate Milvus vector database with pymilvus Python SDK. Use when the user wants to connect to Milvus, create collections, insert vectors, perform similarity search, hybrid search, full-text search, manage indexes, partitions, databases, or RBAC via Python code.
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Structures industry-level credit assessment with cyclicality analysis, regulatory risk, and sector-specific credit metrics. Use when analyzing industry credit conditions, evaluating sector risk, or building industry-level views.
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Cloudflare platform management via Wrangler CLI, Agents SDK (v0.13+), and Browser Rendering API. Deploy Pages, Workers, KV, R2, D1, Queues, Vectorize, Workflows, Hyperdrive. Build stateful AI agents with the full SDK stack — Agent, AIChatAgent, Think, Voice, sub-agents, fibers, HITL, scheduling, observability, Code Mode (Dynamic Worker sandboxes). Budget web scraping via cf_browser.py. Use when deploying to Cloudflare, managing CF infrastructure, configuring wrangler.toml/wrangler.jsonc, building AI agents or chat agents on Workers, adding voice, orchestrating sub-agents, or for cheap web scraping. Triggers: Cloudflare, wrangler, Pages, KV, R2, D1, Workers, Vectorize, Queues, Workflows, Hyperdrive, cf_browser, Browser Rendering, Agents SDK, Code Mode, codemode, MCP, Think, AIChatAgent, Voice agent, sub-agents, fibers, HITL, Dynamic Workers.
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 coding skill for the full MapTiler platform — Cloud REST APIs, MapTiler SDK JS (built on MapLibre GL JS), native mobile SDKs, on-premise infrastructure, and vector tile schemas. USE WHEN the user wants to add a map to a web or mobile app, show locations or routes, display geographic data, build a store locator, create data visualizations on maps, add geocoding or address search, do reverse geocoding, look up elevation, do IP geolocation, fetch weather data, transform coordinates between CRS/EPSG, embed static map images, work with vector tilesets (Planet v4, Buildings, Contours, Outdoor, Ocean, Landcover, Cadastre), write MapLibre style expressions or data-driven styling, render 3D terrain, globe view, or 3D buildings extrusion, use satellite imagery, add markers, popups, heatmaps, or clustering, integrate maps in React, Vue, Svelte, Angular, Next.js, Leaflet, OpenLayers, Cesium, or deck.gl, build native maps on iOS (Swift), Android (Kotlin), Flutter, or React Native, self-host with MapTiler Server or generate tiles with MapTiler Engine CLI, or upload/manage tilesets via the Admin API. Also USE WHEN the user mentions MapLibre GL JS — the SDK extends MapLibre with built-in cloud services, helpers, and session billing.
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Run and analyze molecular dynamics simulations with OpenMM and MDAnalysis. Set up protein and protein-ligand systems with PDBFixer, choose force fields and water models (AMBER14, CHARMM36m, ff19SB, GAFF2, TIP3P), solvate and add ions, run energy minimization, NVT/NPT equilibration and production MD on GPU, then analyze trajectories for RMSD, RMSF, radius of gyration, hydrogen bonds, native contacts, PCA and free energy surfaces. Use this skill for protein stability under mutation, ligand binding-mode and residence-time questions, conformational sampling, membrane proteins, and disordered ensembles. Also trigger on OpenMM, MDAnalysis, mdtraj, Simulation.step, LangevinMiddleIntegrator, PDBFixer, DCD or XTC trajectory, RMSD analysis, or production MD.
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。