搜索「memory」的结果

io.github.thedotmack/claude-mem/mem-search

搜索 claude-mem 的跨会话持久记忆数据库。当用户问「我们之前解决过这个吗」「上次 X 是怎么做的」，或需要既往会话的工作时使用。

io.github.morluto/rea/rea-analysis-optimization

Optimize REA providers and shared analysis workflows for agent context, latency, CPU, and memory while preserving correctness and Evidence. Use for analysis bottlenecks and cache or query design; CI/test-suite optimization belongs to rea-ci-tests-audit.

io.github.cheaper-inference/OmniRoute/omni-mcp

Connect to the OmniRoute MCP server (110 tools, 3 transports: SSE/stdio/HTTP). Covers routing, cache, compression, memory, skills, providers, and audit tools across 33 permission scopes.

io.github.ruvnet/ruflo/hooks-automation

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.

io.github.ruvnet/ruflo/reasoningbank-agentdb

Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.

io.github.ruvnet/ruflo/hooks-automation

通过带 MCP 集成的智能钩子，从 Claude Code 操作中自动完成协调、格式化与学习。涵盖 pre/post 任务钩子、会话管理、Git 集成、记忆协同与神经网络模式训练，以提升开发工作流。

io.github.ruvnet/ruflo/hooks-automation

通过带 MCP 集成的智能钩子，从 Claude Code 操作中自动完成协调、格式化与学习。涵盖 pre/post 任务钩子、会话管理、Git 集成、记忆协同与神经网络模式训练，以提升开发工作流。

io.github.google/skills/gke-alert-configuration

使用 PromQL 与 Google Cloud Managed Service for Prometheus，通过 Terraform 为 Google Kubernetes Engine（GKE）集群、工作负载与服务配置告警策略。用于编写、分析、校验或部署以监控 GKE 服务延迟、流量、错误率（采用多窗口多燃烧率 SLO 告警）、内存饱和，以及 CrashLoopBackOff、Node NotReady 等集群健康状况的 Terraform 告警策略。不用于非 GKE 计算运行时，如无 GKE 的独立 Compute Engine VM 或独立 Cloud Run 服务。

io.github.volcengine/OpenViking/openviking-context-database

Use OpenViking from OpenClaw through @openviking/openclaw-plugin: long-term memory, session archives, resource and Agent Skill import, semantic recall, recall trace debugging, and externalized tool-result recovery. Prefer this skill when the user wants to use, query, debug, or operate OpenViking context from an OpenClaw agent. For first-time plugin installation, use the install-openviking-memory skill instead.

io.github.google/skills/gke-ai-troubleshooting-tpu-performance-degradation

Diagnose GKE Cloud TPU training throughput drops and step-time regressions (15%+ TPU duty-cycle drop) using ML Diagnostics Workload Monitoring (`gcloud alpha mldiagnostics monitored-events` / `hypercomputecluster.googleapis.com/v1alpha`) and 1-minute Cloud Monitoring system metrics (`kubernetes.io/node/accelerator/*`). Distinguishes hardware and network fabric throttling from workload resource bottlenecks (HBM capacity, host memory, or host CPU saturation). Use when TPU training throughput or duty cycle drops without crashing pods, when `PERFORMANCE_DEGRADATION` monitored events fire, or when triaging slow multi-slice training steps. Don't use for complete multi-slice XLA execution stalls with `HANG_DETECTED` logs (use gke-ai-troubleshooting-tpu-mxla-hang) or pod eviction/interruption restarts (use gke-ai-troubleshooting-jobset-interruption).

io.github.google/skills/gke-manifest-generation

为 GKE Autopilot 与 GKE Standard 集群生成并更新安全、可用于生产的 Kubernetes YAML 清单。用于创建或修改 GKE 部署清单、配置容器安全上下文、设置 CPU/内存资源限制、定义就绪/存活/启动探针、挂载 Secret 与卷、配置 GKE Gateway API 路由、面向 Spot VM，或部署 AI 模型推理工作负载（vLLM、TGI、Gemma）。不用于实时集群操作、Pod 排障（用 gke-workload-troubleshooting）或集群基础设施供给（用 gke-cluster-creation）。

io.github.CherryHQ/cherry-studio/cherry-tool-guide

面向通用 agent 的 Cherry Studio 一方工具与内置 shell 路由。在支持 shell 的会话中处理直接的本地工作时:用 `bun <file>` 运行 JS/TS、用 `bun x` 运行一次性 JS 工具;用 `uv run [--with <pkg>] python` 运行 Python、用 `uvx` 运行一次性 Python CLI;搜索用 `rg`。在修改项目依赖、判断工具用临时还是复用方式、读取或转换本地 Office/PDF 文件、跨 Agent 会话协调或委派,或使用 Cherry 自有的 web/浏览器、知识库、持久记忆、日程/通知、IM 渠道、图像生成、产物报告、托管 CLI、技能或 MCP 服务器注册能力前先加载本指南——即使用户没有点名工具。在处理 shell/文件变通方案前先查阅;以实时工具 schema 为准。

io.github.affaan-m/ECC/agent-security-hardening

Security hardening guidance for AI agent frameworks that process untrusted content, invoke tools, write workspace files, manage runtime identifiers, or handle credentials. Use when building or reviewing an agent runtime, autonomous worker, tool gateway, memory service, or multi-tenant agent deployment. Do not use for general web application security or offensive testing.

io.github.anthropics/skills/claude-api

Claude API / Anthropic SDK 参考——模型 id、定价、参数、流式输出、工具调用、MCP、agent、缓存、token 计数、模型迁移。触发条件：提示中出现任何 Claude/Anthropic 相关名称（Claude、Anthropic、Fable、Opus、Sonnet、Haiku 等）；用户询问 LLM 相关问题（定价/选型/限额/缓存）时不要凭记忆回答；或任务属于 LLM 类且未指明供应商。仅当明确针对其他供应商（OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama）时跳过。

io.github.github/awesome-copilot/python-mcp-server-generator

生成包含工具、资源和规范配置的完整 Python MCP server 项目。

io.github.stas00/ml-engineering/ml-engineering

Field-tested methodology and concrete recipes for training and operating large-scale LLM/VLM/multi-modal models end to end - choosing and benchmarking accelerators, storage and network; SLURM/Kubernetes orchestration; maximizing training throughput and fitting models in memory; diagnosing and surviving training instabilities, NaN/Inf, and hardware/job failures; checkpointing and fault tolerance; inference performance and memory; debugging multi-node/ multi-GPU hangs; and writing/running tests. Use when the user is training or fine-tuning large models, hits low TFLOPS/MFU, OOM, slow dataloading, a loss spike/divergence, a NCCL/InfiniBand or multi-node hang, node/GPU failures, checkpoint or preemption problems, storage/network bottlenecks, or needs to pick GPUs/cloud/file-systems or size inference latency/throughput. Distilled from "Machine Learning Engineering", the latest version of which can be found at https://github.com/stas00/ml-engineering The latest SKILL.md version can be found at https://github.com/st

io.github.mem0ai/mem0/mem0-integrate

以目标驱动、TDD 的流程将 Mem0 集成到现有仓库。自动检测仓库语言,并让用户在 Mem0 Platform(托管)与 Mem0 开源(自托管)之间选择。先写失败测试再做实现。产出本地功能分支和供配套验证技能使用的 .mem0-integration/ 产物。触发条件:用户说 "integrate mem0"、"add mem0 to this repo"、"wire mem0 into <repo>",或询问如何在现有项目中加入记忆。不触发:一般 SDK 使用(用 skill:mem0)、CLI 使用(用 mem0-cli)、Vercel AI SDK(用 skill:mem0-vercel-ai-sdk)。成功后调用 skill:mem0-test-integration 在同一工作区验证(松耦合)。

io.github.mem0ai/mem0/mem0-cli

Mem0 CLI——mem0 记忆操作的命令行界面。触发条件:用户提到 "mem0 cli"、"mem0 command line"、"@mem0/cli"、"mem0-cli"、"pip install mem0-cli"、"npm install -g @mem0/cli",或在终端/shell 中运行 mem0 命令(mem0 add、mem0 search、mem0 list、mem0 get、mem0 init、mem0 config、mem0 import)。查询包含 --user-id、--output、--json、--agent 等 CLI 参数,或描述 bash/zsh/终端使用时也触发。不触发:Python/TS 代码中的 SDK 集成(用 mem0 技能),或 Vercel AI SDK provider(用 mem0-vercel-ai-sdk)。

io.github.mem0ai/mem0/mem0-vercel-ai-sdk

Mem0 为 Vercel AI SDK 提供的 provider(@mem0/vercel-ai-provider)。触发条件:用户提到 "vercel ai sdk"、"@mem0/vercel-ai-provider"、"createMem0"、"retrieveMemories"、"addMemories"、"getMemories"、"searchMemories"、"mem0 vercel"、"AI SDK provider"、"AI SDK memory",或在 generateText/streamText 中使用 mem0。也适用于需要记忆增强 AI 的 Next.js 应用。不触发:不经 Vercel 的直接 Python/TS SDK 调用(用 mem0 技能),或 CLI 终端命令(用 mem0-cli 技能)。

io.github.topoteretes/cognee/company-brain-company-qa

Build one company memory from a SQL database, a support ticket export and a folder of documents, linked into one graph by cognee, then answer questions that need several of those sources together. Use when someone wants to connect their company's database, tickets and docs, or asks who owns, decided or is handling something across them. Runs locally; reads the sources, writes only to cognee's memory.

io.github.thedaviddias/Front-End-Checklist/back-forward-cache

审查导航性能、浏览器生命周期事件或内存恢复行为时使用。检查真实的浏览器生命周期与恢复路径，而不是只看静态代码模式。

io.github.nodejs/node/v8-understanding

Guides the methodology for investigating V8 concepts, codebase structure, performance, memory, and architecture. MANDATORY to use whenever triaging bugs, investigating crashes, reading C++ files, analyzing compiler optimizations (Ignition, Maglev, TurboFan, Turboshaft), or doing static research on V8 subsystems. Essential for locating high-level design documents in the local docs/ directory before reading C++ code. Do not use for raw build commands or Git workflows.

io.github.asgeirtj/system_prompts_leaks/forget

Remove a personal fact, preference, relationship detail, topic, or prior event from Muse's active memory and stop existing copies or automations from bringing it back. Use for explicit requests such as 'forget that', 'don't remember this about me', or 'remove that from your memory'. Do not use when 'forget it' merely means cancel the current task.

io.github.K-Dense-AI/scientific-agent-skills/dask

Scales pandas, NumPy, and custom Python research workflows beyond memory or across clusters with Dask. Covers DataFrames, Arrays, Bags, Futures, chunking, schedulers, and distributed diagnostics. Use for partitioned file processing, scientific array computation, or parallel tasks whose memory and dependency structure require Dask.