「asi」の検索結果

Python fuzzing with Atheris for discovering vulnerabilities in Python code.

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。

Clarify requirements before implementing. Use when serious doubts araise.

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。

Measure encoding/decoding throughput across Syrup implementations. This skill provides bandwidth benchmarks for comparing serialization performance.

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 biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical research including CRISPR screening design, single-cell RNA-seq analysis, ADMET prediction, GWAS interpretation, rare disease diagnosis, or lab protocol optimization. Leverages LLM reasoning with code execution and integrated biomedical databases.

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。

Brain-Computer Interface with colored operad security boundaries. Maximally isolated EEG/neural data processing via VM→Container→Process enclosure with GF(3) conservation for Agent-O-Rama neural pathways.

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。

This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.

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ANIMA as limit construction over condensed skill applications. Formalizes prediction markets as belief ANIMAs, structure dishes as condensation media, and impact as equivalence class change. Use for understanding agency at maximum entropy, compositional world modeling, or applying Scholze-Clausen condensed mathematics to AI.

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。

Reality tech (AR/VR/XR). Build and ship spatial experiences (WebXR/OpenXR/Unity/Unreal) with strong defaults for interaction, performance, comfort, privacy, and deployment.

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。

Guided workflow for building custom AI agents using the OpenHands Software Agent SDK. Use when you want to create a new agent through an interactive interview process that gathers requirements and generates implementation plans.

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。

Tour of Alice's heavily-customized terminal Emacs — Causal transients, Worlding org, proof tooling, MLX chat, voice, and clipboard.

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When the user wants to set up, improve, or audit analytics tracking and measurement. Also use when the user mentions "set up tracking," "GA4," "Google Analytics," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "analytics implementation," or "tracking plan." For A/B test measurement, see ab-test-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。

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。

Execute trades on Aptos mainnet with price-triggered profit-taking and dip-buying strategies. Includes wallet management, transaction signing, and DEX swaps via Liquidswap. Use when automating APT trading, checking balances, or executing swaps.

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。

Amazon product search, cart management, price tracking, and shopping list via Playwright + DuckDB MCP server

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Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.

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。

Primary Aptos testnet wallet for transaction origination. Use when initiating test transactions.

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Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, or chat applications.

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。

Interruption pattern detection and retrieval from Amp thread history. Use for analyzing tool rejection patterns and improving agent behavior.

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Combines AMP thread export with GF(3)-classified continuation for skill orchestration. Export threads as markdown, classify continuation choices as {-1:reductive, 0:neutral, +1:generative}, and fork parallel execution paths.

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。

Persist and retrieve repository-specific knowledge using AGENTS.md files. Use when you want to save important information about a codebase (build commands, code style, workflows) for future sessions.

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。

ALIFE 2025 Proceedings - 337 pages, 80+ papers on artificial life, evolution, emergence, cellular automata, neural networks, agent-based models. Full Mathpix extraction with equations and figures.

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Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.

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。

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems.

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。

Comprehensive Artificial Life skill combining ALIFE2025 proceedings, classic texts (Axelrod, Epstein-Axtell), ALIEN simulation, Lenia, NCA, swarm intelligence, and evolutionary computation. 337 pages extracted, 80+ papers, 153 figures.

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。