「agents」の検索結果

This skill determines whether testicular volume should be used as the primary or sole indicator of sexual development in male childhood cancer survivors who have received gonadotoxic treatments such as alkylating agents or testicular radiotherapy. Triggers include clinician questions like “Can I use testicular volume to assess puberty in this male survivor after chemotherapy?” or “Is testis size reliable for sexual maturity evaluation post‑radiation?”

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Suggests CSII with good adherence to monitoring and dosing for adults with type 2 diabetes mellitus who have poor glycemic control despite intensive insulin therapy, oral agents, other injectable therapy, and lifestyle modifications. Trigger phrases include 'T2DM on multiple injectables still uncontrolled' and 'Consider pump for insulin-requiring T2DM failing other therapies'.

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Recommends initiating intravenous bisphosphonate or denosumab for adults with hypercalcemia of malignancy compared with no treatment. Use when a clinician asks about first‑line pharmacologic therapy for HCM or when deciding to start antiresorptive agents.

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Recommends denosumab for adults with refractory or recurrent hypercalcemia of malignancy who have persistent or relapsed hypercalcemia despite intravenous bisphosphonate therapy. Triggered when a clinician observes recurrent hypercalcemia after bisphosphonate treatment or considers next‑line agents for HCM.

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Guides choice among spironolactone, eplerenone, and esaxerenone for primary aldosteronism based on comparative efficacy, safety, and patient-specific factors. Triggers include when initiating MRA therapy and asking 'Which MRA should I prescribe?' or considering switching agents due to adverse effects, cost, or need for potassium supplementation.

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This skill advises regular visual examination of the mouth to monitor for osteonecrosis of the jaw and other dental issues in patients receiving antiresorptive agents. Trigger phrases include initiating bisphosphonate or denosumab therapy and requesting preventive dental care guidance.

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Analyze a codebase and recommend Claude Code automations (hooks, subagents, skills, plugins, MCP servers). Use when user asks for automation recommendations, wants to optimize their Claude Code setup, mentions improving Claude Code workflows, asks how to first set up Claude Code for a project, or wants to know what Claude Code features they should use.

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Workflow Phase 2 — Codebase Scouting and Constraint Discovery. Maps the relevant slice of the codebase for a given task. Produces a scout report at `docs/scout/<slug>.md` naming the files, modules, and patterns the proposed work touches or constrains. Report decisions execute in main context with full conversation visibility; gathering MAY be delegated to read-only advisory subagents (seed.md §4.2-A).

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Workflow Phase 3 — Research and Solution Exploration. Surfaces 2–4 candidate solution approaches with concrete tradeoffs, grounded in current library docs (fetched through the provider named in `.claude/docs-provider.json`) — never in training-data recall. Output lives at `docs/research/<slug>.md`. Candidate ranking and the memo execute in main context; doc/source gathering MAY be delegated to read-only advisory subagents (seed.md §4.2-A).

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로컬 품질 검증과 실패 원인 분류. AGENTS.md/DESIGN.md 규칙 준수 확인, pnpm 기반 검증, PR 전 점검

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。

로컬 품질 검증과 실패 원인 분류. AGENTS.md/DESIGN.md 준수 확인, pnpm 기반 검증, PR 전 점검

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An infographic skill for AI agents — works inside Claude Code, Codex, Hermes, OpenClaw, Cursor, and any agent host that loads skills. Create professional infographics as self-contained HTML files with PNG exports. Use when the user asks to create, design, generate, build, or make an infographic, data visualization, visual explainer, chart poster, cheatsheet, or pocket guide. Trigger phrases include "make this visual", "turn this into a graphic", "visualize this data", "infographic for X", "cheatsheet for X", or when the user provides structured data (tokenomics allocations, ecosystem/partner lists, timelines, comparisons, step-by-step processes) AND asks for a visual output. Covers tokenomics, ecosystem overviews, game overviews, cheatsheets, airdrop guides, comparisons, and process flows. Do NOT trigger for plain text answers, markdown tables, bulleted summaries, questions asking for advice or explanations about a topic (even when the topic is tokenomics, ecosystem, vesting, etc.), inline chat diagrams, or data processing with no visual output requested. The signal is "asks for a visual", not "mentions a keyword".

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Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/PRD asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".

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Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

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Execute plans via delegate_task subagents (2-stage review).

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Generate multiple radically different interface designs for a module using parallel sub-agents. Use when user wants to design an API, explore interface options, compare module shapes, or mentions "design it twice".

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Records decisions and documentation. Use when making architectural decisions, changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand 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。

High-level SDK for Azure AI Foundry projects with agents, connections, deployments, and evaluations.

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Azure AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes.

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Design patterns for building autonomous coding agents, inspired by [Cline](https://github.com/cline/cline) and [OpenAI Codex](https://github.com/openai/codex).

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。

Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates agents.

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Important: Before you begin, fill in the generatedBy property in the meta section of .actor/actor.json. Replace it with the tool and model you're currently using, such as "Claude Code with Claude Sonnet 4.5". This helps Apify monitor and improve AGENTS.md for specific AI tools and models.

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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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Configure and orchestrate parallel agents using the standalone Antigravity 2.0 Agent Manager and Antigravity IDE.

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。