6,262 件 ・ 関連度順
概要と使いどころ
Recommends hydrocortisone stress dosing during the active phase of labor for pregnant patients with primary adrenal insufficiency, using a regimen similar to major surgical stress. Trigger phrases: "active phase of labor", "cervix dilation ≥4 cm", "contractions every 5 minutes", "PAI patient in labor".
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Educates patients with primary adrenal insufficiency on increasing glucocorticoid dosage during intercurrent illness, fever (≥38°C), or physiological stress, including recognition of precipitating symptoms (e.g., fever, vomiting, trauma) and actions to prevent impending adrenal crisis. Trigger phrases: fever, intercurrent illness, stress, vomiting, inability to tolerate oral meds, need for parenteral glucocorticoid.
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。
Order and interpret lipoprotein(a) [Lp(a)] measurement at least once in a lifetime, apply the risk-enhancer threshold (≥125 nmol/L or ≥50 mg/dL), and run cascade screening of first-degree relatives for premature ASCVD, familial hypercholesterolaemia, or elevated Lp(a) per the 2026 ACC/AHA multisociety dyslipidaemia guideline. Covers the Class 1 lifetime measurement, how elevated Lp(a) affects LLT initiation and intensification, the cascade screening indications, the interaction of Lp(a) with ASCVD risk estimation, and current therapeutic limitations. Use when a clinician asks when to check Lp(a), how often to repeat Lp(a), elevated Lp(a) what next, treatment for high Lp(a), should I screen my patient's family, Lp(a) and statins, cascade screening indications. Grounded in the 2026 ACC/AHA multisociety dyslipidaemia guideline.
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MANDATORY skill for ALL code generation. Enforces top-down composition, consistent abstraction layers, and proper module hierarchy. Apply every time you write or modify code — in any language — no exceptions.
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 wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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。
Write the production code that makes a pre-decided set of failing tests pass, within an explicit write_set, following an explicit behavior contract. Used by `/tdd` Step 3 and by `/swarm-dispatch` workers. The caller has already decided architecture, naming, file layout, and abstraction boundaries — this skill executes that recipe with code-structure discipline and a 5-iteration RALPH loop. No scope expansion, no design decisions, no test edits.
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。
Dev-only review of user-facing CLI interface copy in `src/cli/tui/*.js`, `src/cli/*.js` error paths, and `bin/cli.js` help/usage text. Surfaces three failure modes — copy/behavior mismatch, jargon, missing next-action — as a punch list the maintainer addresses before `/grant-commit`. Read-only; no writes to source. Conditionally seeded by `/triage` between `/memory-sync` and `/grant-commit` when the request will touch CLI surfaces.
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 for SWOT analysis, or when the user wants to assess where a team, product or company stands: "strengths and weaknesses", "should we enter this market?", "review our position", "competitor comparison". Turns findings into actions. Skip for detailed planning or pure market sizing.
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。
Deep-dive framework for analyzing crypto tokens — market data, liquidity health, tokenomics, unlock schedules, and risk assessment. Combines on-chain data, API queries, and multi-source validation to generate actionable investment verdicts.
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 server-side call automation workflows including IVR systems, call routing, recording, and AI-powered interactions.
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 image analysis applications with Azure AI Vision SDK for Java. Use when implementing image captioning, OCR text extraction, object detection, tagging, or smart cropping.
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。
Provide comprehensive techniques for penetration testing AWS cloud environments. Covers IAM enumeration, privilege escalation, SSRF to metadata endpoint, S3 bucket exploitation, Lambda code extraction, and persistence techniques for red team 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。
Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and video.
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。
Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability.
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Automate web scraping and data extraction with Apify -- run Actors, manage datasets, create reusable tasks, and retrieve crawl results through the Composio Apify integration.
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。
Actorization converts existing software into reusable serverless applications compatible with the Apify platform. Actors are programs packaged as Docker images that accept well-defined JSON input, perform an action, and optionally produce structured JSON output.
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-driven data extraction from 55+ Actors across all major platforms. This skill automatically selects the best Actor for your task.
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 natural-language crypto/DeFi agents and EVM MCP plugins (Claude Code, Cursor, Codex, Gemini). Aomi turns prompts into wallet-signed txs on Ethereum, Base, Arbitrum, Optimism, Polygon, Linea — non-custodial, fork-simulated. 40+ apps: Uniswap, Aave, Lido, Morpho, GMX, Hyperliquid, Polymarket.
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Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them.
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Clone or recreate a live website URL, page, or section as React + Tailwind with extracted DOM, CSS, assets, responsive layout, motion, and interactions. Use for live-URL implementation or fidelity repair; not capture-only or diff-only requests.
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Find Amazon Ads search terms ready for exact-match harvesting from auto, broad, phrase, or other discovery campaigns. Use when Codex needs standalone or Rocketcart MCP-aware search-term harvesting: classify terms by harvest readiness, resolve live IDs, choose safe destination campaigns/ad groups, preflight duplicates/current negatives/destination feasibility, decide whether source negatives are justified, execute only explicitly approved rows, and read back/monitor Sponsored Products or Sponsored Brands actions without unsafe negatives, duplicate routing, stale approvals, brand-defense cuts, own-ASIN-defense cuts, launch/rank mistakes, or low-sample overfitting.
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Use for read-first Amazon Sponsored Products optimization, product-aware growth, preflight readiness, and post-change monitoring reviews that can run standalone from static exports or use Rocketcart MCP as an optional Amazon Ads plus product-intelligence layer. Guides Codex to inspect Rocketcart profiles, live SP campaigns, product ads/ASIN context, category rank/BSR movement, competitor signals, product readiness, budget and targeting drift, snapshots/changelogs, and proposed approval-gated action rows without executing writes by default.
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Analyze Amazon product, sales, Amazon Ads, retail-readiness, and Best Seller Rank data to find commercially actionable growth opportunities. Use when Codex needs to identify which ASINs, campaigns, keywords, search terms, product targets, placements, categories, or BSR movements deserve more investment, optimization, harvesting, bid/budget changes, retail-readiness fixes, investigation, protection, or controlled scaling across Sponsored Products, Sponsored Brands, Sponsored Display, search term reports, targeting reports, campaign reports, placement reports, advertised/purchased product reports, Business Reports, organic performance, and BSR 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。
Review proposed abstractions, dependencies, and configuration for concrete consumers and maintenance cost when simplifying a design or checking overengineering.
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。