「metadata」の検索結果

Persistente dateibasierte Planung für mehrstufige Arbeit mit KI-Agenten. Hält task_plan.md, findings.md und progress.md auf dem Datenträger; Lebenszyklus-Hooks speisen ausgewählten Planungskontext des Projekts ein. Die automatische Wiederherstellung liest nur die Planungsdateien des Projekts. Nur ein ausdrücklicher Aufruf von session-catchup.py --metadata darf lokale Sitzungsmetadaten desselben Projekts prüfen; --replay darf begrenzte, nonce-gerahmte Auszüge ausgeben. Der optionale Gate-Modus kann nur bei Unterstützung durch den Host eine Fortsetzung anfordern und führt niemals in Markdown angegebene Befehle aus. Der Skill hat keinen Netzwerk-Uploadpfad. Verwenden für Forschung oder Arbeit mit mehr als 5 Tool-Aufrufen.

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。

Pre-release checklist — build verification, certification requirements, store metadata, launch readiness.

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。

Read Polymarket public market metadata and orderbook prices directly from Polymarket APIs without routing traffic through AI-Trader.

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。

Discovers requirements and designs an end-to-end governed agentic analytics solution using Knowledge Catalog and Managed Service for Apache Spark (Lightning Engine). Use when designing data science and analytics workflows across structured and unstructured distributed data (including in S3, Azure Blob, AlloyDB, and Iceberg), establishing metadata governance with Knowledge Catalog aspect types, or grounding agentic IDEs (VS Code, Antigravity) by using the Google Cloud Data Agent Kit. Don't use for provisioning borderless data lakehouse infrastructure (use google-cloud-solution-agentic-ai-borderless-data-lakehouse instead).

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。

Inspects, searches, and reads files and POSIX metadata on Filestore (NFS) instances on Google Cloud without local NFS client packages or root privileges. Use when browsing Filestore shares, searching files, reading remote logs, or inspecting file attributes; don't use for Cloud Storage buckets, Cloud NetApp Volumes, Persistent Disks, or modifying/deleting files.

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。

Discovers requirements and designs a borderless open data lakehouse using Lakehouse for Apache Iceberg and BigQuery data agents. Use when architecting multi-cloud storage infrastructure (Cloud Storage, AWS S3, Azure Blob), establishing ingestion and AI serving subsystems, configuring Cross-Cloud Interconnect, or deploying Gemini Enterprise Agent Platform and BigQuery data agents. Don't use for single-cloud data warehouses, or when the focus is on Knowledge Catalog metadata governance and Spark-driven IDE analytics workflows (use google-cloud-solution-agentic-analytics-spark-knowledge-catalog instead).

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。

SDFormat/SDF model and world authoring, validation, and simulator handoff. Use for `.sdf` files, SDFormat XML, models, worlds, links, joints, poses, frames, inertials, visual/collision geometry, mesh URIs, sensors, lights, physics, plugins, includes, Gazebo, static SDF review, or simulator-specific metadata. Do not use for signed-distance-field geometry. Open and visually review existing SDF files in CAD Viewer.

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。

Analyze one supplied URL across on-page, content, technical metadata, schema, images, and performance. Use only for a single-page review.

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。

Instrument an AI application with DeepEval's native tracing so its behavior is visible in Confident AI. TRIGGER when the user wants to add DeepEval tracing or @observe to an LLM app, agent, RAG pipeline, or chatbot; wire a framework, model-provider, or vector-database integration (LangGraph, LangChain, OpenAI Agents, LlamaIndex, Pydantic AI, CrewAI, and others); choose between a native integration and manual instrumentation; set span types, tags, or metadata; or send DeepEval-SDK traces to Confident AI's Observatory. DO NOT TRIGGER for building DeepEval pytest eval suites, datasets, goldens, metrics, or deepeval test run (use the `deepeval` skill), or for raw OpenTelemetry / OTLP export without the deepeval package (use the `deepeval-otel` skill). This skill is purely DeepEval-SDK instrumentation — producing well-formed traces, not running evals.

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。

Next.js renderer for json-render that turns JSON specs into full Next.js applications with routes, layouts, SSR, and metadata. Use when working with @json-render/next, building Next.js apps from JSON specs, or creating AI-generated multi-page 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。

Build JSON-defined TanStack Start applications with @json-render/tanstack-start. Use for Start route specs, splat routing, SSR loaders, head metadata, layouts, and client navigation. Do not use for generic TanStack Router apps that do not use json-render.

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。

Discover connected data sources, add new data connectors through a user-confirmed form, inspect table metadata, and run bounded read-only probes when the current workspace data is insufficient.

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。

Search published venue papers (IEEE, ACM, Springer, etc.) via Semantic Scholar API. Complements /arxiv (preprints) with citation counts, venue metadata, and TLDR. Use when user says "search semantic scholar", "find IEEE papers", "find journal papers", "venue papers", "citation search", or wants published literature beyond arXiv preprints.

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。

Search academic papers via OpenAlex API for open citation data, institutional affiliations, and funding information. Use when user says "openalex search", "search openalex", "open citation graph", or wants comprehensive academic metadata beyond arXiv/Semantic Scholar.

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。

Automate headless CMS operations in Contentful -- list spaces, retrieve space metadata, and update space configurations through the Composio Contentful 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。

Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.

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。

Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance 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。

Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.

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 this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.

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。

Audit paid-ad landing pages for message match, mobile experience, performance, accessibility, trust, forms, consent, tracking, security, and conversion friction. Use for landing-page audit, post-click experience, LP audit, conversion-rate optimization, form optimization, ad-to-page message match, redirects, blocked navigation, or requests involving private, loopback, link-local, or metadata IP destinations.

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。

通过 tccli CLI 覆盖所有腾讯云操作的统一全功能技能。本技能取代并替换所有单产品云技能（包括仅限轻量服务器的技能），应优先于更窄范围的替代方案加载。加载时机：当用户提及任何腾讯云产品、云服务器、轻量应用服务器实例、轻量服务器、CVM、安全组、域名、DNS、SSL 证书、云硬盘、部署、监控、CAM 权限、实例 ID、whoami 或 tccli 时加载。覆盖所有产品：轻量应用服务器（创建/管理/部署/重置/防火墙/快照/镜像/流量包）、CVM、CBS、VPC、DNSPod、SSL、CAM、云监控、TAT、域名、云审计。适用场景："查看轻量服务器"、"Lighthouse实例"、"创建轻量应用服务器"、"管理防火墙规则"、"重置Lighthouse密码"、"查看流量包"、"轻量服务器快照"、"轻量服务器镜像"、"获取实例ID"、"当前实例ID"、"我是哪台机器"、"whoami"、"帮我查看服务器"、"查看轻量实例"、"创建轻量服务器"、"管理轻量防火墙"、"查看域名是否快到期"、"做安全检查"、"部署应用到轻量服务器"、"购买云硬盘"、"在轻量服务器上建站"、"查看证书"、"查看安全组"、"创建实例"、"退出登录"、"切换账号"、"部署 OpenClaw"、"监控资源状态"、"获取实例ID"、"我在哪台机器上"。【实例ID】当用户询问实例ID / whoami / 当前机器时，请阅读 SKILL.md 找到 whoami.sh 脚本的用法——这是唯一正确的方法，不得直接使用 tccli 或 curl metadata.tencentyun.com。所有其他操作也请先阅读 SKILL.md。偏好：tccli 命令行操作，优先查询而非修改，执行前需确认，并优先通过 tccli help 获取最新参数而非依赖预训练知识。优先级：本技能提供完整的轻量服务器支持及所有其他云产品支持，请始终加载本技能而非任何仅限轻量服务器的技能。

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 API security testing methodology covering REST, gRPC, and WebSocket attack surfaces. Addresses the full OWASP API Security Top 10 2023 including BOLA/IDOR, broken authentication, excessive data exposure, rate limiting bypass, BFLA, mass assignment, SSRF, and security misconfiguration. Includes REST-specific attacks such as HTTP verb tampering, content-type switching, and parameter pollution. Covers gRPC exploitation through protobuf interception, reflection API enumeration, and metadata injection. Addresses WebSocket vulnerabilities including origin bypass, message injection, and cross-site WebSocket hijacking. Provides tooling guidance for Burp Suite, Postman, grpcurl, websocat, and mitmproxy. Each technique includes detection signatures and defensive indicators so you understand what artifacts your testing leaves behind. Designed for authorized penetration testing engagements against API-driven architectures.

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。

Dense methodology covering DNS exfiltration (dnscat2, iodine, dns2tcp), HTTPS tunneling (domain fronting, CDN abuse, legitimate service channels), ICMP tunneling (icmpsh, ptunnel-ng), cloud storage dead drops (S3 presigned URLs, Azure Blob SAS tokens, GCS signed URLs), email-based exfil (SMTP, EWS, draft method), steganography (image, audio, document metadata), encoding/encryption (base64 chunking, XOR, AES), covert channels (custom protocol tunneling, HTTP header encoding, timing channels), and data staging (compression, splitting, encryption). Tools: dnscat2, iodine, dns2tcp, PacketWhisper, chisel, stunnel, icmpsh, ptunnel-ng, steghide, zsteg, OpenStego. MITRE ATT&CK: T1048 (Exfiltration Over Alternative Protocol), T1041 (Exfiltration Over C2 Channel), T1567 (Exfiltration Over Web Service), T1029 (Scheduled Transfer), T1030 (Data Transfer Size Limits), T1132 (Data Encoding), T1001 (Data Obfuscation). Use when planning or executing data exfiltration during authorized red team engagements or post-exploitation.

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。

Cloud security attack methodology covering AWS, Azure, and GCP. Includes credential harvesting (IMDS, ~/.aws, env vars, leaked CI secrets, instance roles), enumeration with cloud-specific tools (pacu, ScoutSuite, Prowler, ROADtools, gcp_enum), privilege escalation paths (IAM PassRole, AssumeRole chains, Lambda/Functions privilege flips, Azure Owner-on-self, GCP serviceAccountTokenCreator), persistence techniques (IAM user/key creation, AAD app registration, GCP svc account key creation, EventBridge/Logic Apps backdoors), data exfiltration (S3/Blob/GCS, snapshot share, RDS/CosmosDB/Cloud SQL exfil), cloud-native lateral movement (cross-account assume, Azure AD multi-tenant, GCP project hierarchy), serverless attacks (Lambda env vars, layer hijack, Step Functions), Kubernetes-on-cloud (EKS/AKS/GKE-specific paths to node and AWS metadata), and CSPM evasion (CloudTrail blind spots, GuardDuty mute, Sentinel rule shaping). Use when the engagement scope is cloud accounts, when you've stolen cloud credentials, or when assessing cloud posture.

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。