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「agent memory」の検索結果

803 件 ・ 関連度順

概要と使いどころ

Explain and configure individual spacing algorithms using student performance data and forgetting curves. Use when personalising retention schedules in adaptive learning platforms.

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。

GarethManning/education-agent-skills8472026年8月29日 更新

Achieve aggressive v3 performance targets: 2.49x-7.47x Flash Attention speedup, 150x-12,500x search improvements, 50-75% memory reduction. Comprehensive benchmarking and optimization suite.

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。

ruvnet/agentic-flow8182026年10月12日 更新

Automated coordination, formatting, and learning from Claude Code operations using intelligent hooks with MCP integration. Includes pre/post task hooks, session management, Git integration, memory coordination, and neural pattern training for enhanced development 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。

ruvnet/agentic-flow8182026年10月12日 更新

Improve the agent itself, or audit its recent performance - better skills, prompts, workflows, and config, plus a quality/reliability/memory-hygiene review of what it did and what failed

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。

aeonfun/aeon7712026年10月12日 更新

Write and read the between-session handoff file so a fresh agent with no memory can pick up where the last one stopped without re-deriving context. Structured prose, not JSON — the model writes prose better.

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。

Archive228/loopkit7552026年7月15日 更新

Design or audit a repo-local markdown knowledge graph with wiki links, source-code backlinks, drift checks, and searchable sections. Use when AGENTS.md/CLAUDE.md is too flat for a large codebase or when a custom harness needs durable structured project memory.

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。

stevesolun/ctx5882026年10月4日 更新

Containerize NestJS apps with multi-stage Docker builds, tune Node.js memory, and implement graceful shutdown hooks. Use when writing Dockerfiles, configuring K8s deployments, or adding shutdown hooks for NestJS.

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。

HoangNguyen0403/agent-skills-standard5732026年10月11日 更新

Write Pest feature tests with RefreshDatabase, mock external services, and create test data with Eloquent Factories in Laravel. Use when adding HTTP tests, configuring SQLite in-memory test database, or mocking payment services.

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。

HoangNguyen0403/agent-skills-standard5732026年10月11日 更新

Optimize Flutter widget rebuilds, memory usage, rendering, and scrolling performance. Use when diagnosing jank, reducing rebuilds, or improving list performance—not performance tests, monitoring setup, or API optimization.

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。

HoangNguyen0403/agent-skills-standard5732026年10月11日 更新

Apply SAP HANA database standards for SQL parameterization, in-memory engine optimization, dynamic IN query chunking, column aliasing on joins, and datatype casting. Use when writing SQL for SAP HANA, optimizing HANA queries, or diagnosing HANA driver errors.

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。

HoangNguyen0403/agent-skills-standard5732026年10月11日 更新

Enforce universal standards for high-performance development. Use when profiling bottlenecks, reducing latency, fixing memory leaks, improving throughput, or optimizing algorithm complexity in any language.

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。

HoangNguyen0403/agent-skills-standard5732026年10月11日 更新

Use for authorized security assessment of LLM applications and AI agents, including prompt injection, tool abuse, RAG exposure, memory poisoning, and model supply-chain risks.

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。

coco-research/coco5582026年10月12日 更新

Use when the user says 'cognee recall', 'search memory', 'what do we know about', 'find related', or 'graph search'. Runs semantic, graph, and lexical search across the Cognee knowledge graph and injects results as agent context.

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。

coco-research/coco5582026年10月12日 更新

mot

無料

System health check (MOT) for skills, agents, hooks, and memory

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。

vibeeval/vibecosystem5332026年8月9日 更新

Daily tech product and open-source discovery digest. Fetches today's Product Hunt leaderboard and GitHub Trending top 10, then curates a personalized briefing in the user's preferred language using their memory/profile to highlight items most relevant to them. Use this skill whenever the user says "daily hunt", "今日猎奇", "tech digest", "daily digest", "what's trending", "今天有什么新产品", "PH today", "show me today's launches", "GitHub trending", "今日趋势", "morning briefing", "tech briefing", "daily brief", or any combination asking about Product Hunt + GitHub Trending together. Also trigger when the user asks about new product launches, trending repos, or wants a curated tech news digest. Even casual phrasing like "what's new in tech today" or "有什么好玩的项目" should trigger this skill.

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。

MagicCube/agentara5162026年5月11日 更新

heartbeat

無料

Proactive intelligence pulse — scans user's memory files (USER.md, SOUL.md) to identify current interests, investments, projects, and concerns, then performs targeted web searches to find noteworthy updates. Returns a concise briefing if something deserves attention, or `[SKIPPED]` if nothing warrants interruption. Use this skill when the system needs to check if there's anything worth proactively notifying the user about — like a scheduled heartbeat check, a "what's new" sweep, or when the user asks "anything I should know?", "what did I miss?", or "any updates?". Also triggers on requests like "check my interests", "scan for news", "morning briefing", or "pulse check".

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。

MagicCube/agentara5162026年5月11日 更新

Use when the user is investigating QML / Qt Quick performance — both vague complaints ("the UI feels laggy", "this is slow", "frames are dropping", "the app stutters") and explicit asks to profile, find hotspots, or optimize bindings, signals, or rendering. Runs qmlprofiler on a 2D QML application, parses the .qtd trace, and analyzes hotspots against the source with frame-time, memory, and pixmap-cache summaries. Does NOT cover Qt Quick 3D.

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。

TheQtCompanyRnD/agent-skills4742026年10月8日 更新

Optimize code performance through iterative improvements (max 2 rounds). Benchmark execution time and memory usage, compare against baseline implementations, and generate detailed optimization reports. Supports C++, Python, Java, Rust, and other languages.

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。

bytedance/agentkit-samples4702026年10月12日 更新

Extract lessons from the current session, or sweep the project's past sessions when asked, and route them to the appropriate knowledge layer (project AGENTS.md, auto memory, existing skills, or new skills). Use when the user asks to "self-improve", "distill this session", "distill past sessions", "sweep past sessions", "extract lessons from all sessions", "save learnings", "update CLAUDE.md with what we learned", "capture session insights", "remember this for next time", "extract lessons", "update skills from session", or "what did we learn".

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。

tobihagemann/turbo4092026年10月12日 更新

Stop and consult this skill whenever your response would include specific facts about Anthropic's products. Covers: Claude Code (how to install, Node.js requirements, platform/OS support, MCP server integration, configuration), Claude API (function calling/tool use, batch processing, SDK usage, rate limits, pricing, models, streaming), and Claude.ai (Pro vs Team vs Enterprise plans, feature limits). Trigger this even for coding tasks that use the Anthropic SDK, content creation mentioning Claude capabilities or pricing, or LLM provider comparisons. Any time you would otherwise rely on memory for Anthropic product details, verify here instead — your training data may be outdated or wrong.

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。

syahiidkamil/Software-Engineer-AI-Agent-Atlas4012026年6月25日 更新

Chunked N-D arrays with compression and cloud storage. NumPy-style indexing. Backends: local, S3, GCS, ZIP, memory. Dask/Xarray integration for parallel and labeled computation. For lineage use lamindb; for labeled arrays use xarray.

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。

jaechang-hits/SciAgent-Skills3762026年9月29日 更新

Fast in-memory DataFrame with lazy evaluation, parallel execution, Arrow backend. Use for tabular data in RAM (1–100 GB) when pandas is too slow. Expression API: select, filter, group_by, joins, pivots, window. Lazy mode enables predicate/projection pushdown. Reads CSV, Parquet, JSON, Excel, DBs, cloud. Larger-than-RAM: Dask; GPU: cuDF.

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。

jaechang-hits/SciAgent-Skills3762026年9月29日 更新

Build or revise private, cited Markdown notes from the user's WeChat history in the current agent session. Use for a maintained personal wiki or incremental notes; use greenbubbles-context for a one-off lookup or summary.

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。

bojieli/greenbubbles3722026年10月3日 更新

Best practices for Docker-based ROS2 development including multi-stage Dockerfiles, docker-compose for multi-container robotic systems, DDS discovery across containers, GPU passthrough for perception, and dev-vs-deploy container patterns. Use this skill when containerizing ROS2 workspaces, setting up docker-compose for robot software stacks, debugging DDS communication between containers, configuring NVIDIA Container Toolkit for GPU workloads, forwarding X11/Wayland for rviz2 and GUI tools, or managing USB device passthrough for cameras and serial devices. Trigger whenever the user mentions Docker with ROS2, docker-compose for robots, Dockerfile for colcon workspaces, container networking for DDS, devcontainer for ROS2, multi-stage builds for ROS2, or deploying ROS2 in containers. Also trigger for CI/CD with Docker-based ROS2 builds, CycloneDDS or FastDDS configuration in containers, or shared memory in Docker. Covers Humble, Jazzy, and Rolling distributions across Ubuntu 22.04 and 24.04 base images.

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。

arpitg1304/robotics-agent-skills3722026年8月12日 更新