「connector」の検索結果

Deploy and use the Exasol Text AI Extension (TXAIE) with notebook-connector. Covers `deploy_license`, `initialize_text_ai_extension`, the `PYTHON3_TXAIE` language container, the Extraction API classes `StandardExtractor`, `NamedEntityExtractor`, `TopicClassifierExtractor`, `PipelineExtractor`, and `BranchExtractor`, named-entity, zero-shot classification, and feature extraction runs, default-model installation, and result-table querying such as `TXAIE_AUDIT_LOG`.

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。

Deploy and use the Exasol Transformers Extension (TE) for NLP inference inside Exasol with notebook-connector. Covers `initialize_te_extension`, `deploy_scripts`, `PYTHON3_TE` language-container activation SQL, Hugging Face model-installation workflows, and the current TE SQL UDF surface.

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。

Evidence-first automation inventory and overlap audit workflow for ECC. Use when the user wants to know which jobs, hooks, connectors, MCP servers, or wrappers are live, broken, redundant, or missing before fixing anything.

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。

Deploying Palo Alto Networks Prisma Access for SASE-based zero trust network access using GlobalProtect agents, ZTNA Connectors, security policy enforcement, and integration with Strata Cloud Manager for unified security management.

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 covers deploying Microsoft Sentinel as a cloud-native SIEM and SOAR platform for centralized security operations. It details configuring data connectors for multi-cloud log ingestion, writing KQL detection queries, building automated response playbooks with Logic Apps, and leveraging the Sentinel data lake for petabyte-scale threat hunting across AWS, Azure, and GCP security telemetry.

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Use when user asks to "build a Solana dapp", "write an Anchor program", "create a token", "debug Solana errors", "set up wallet connection", "test my Solana program", "deploy to devnet", or "explain Solana concepts" (rent, accounts, PDAs, CPIs, etc.). End-to-end Solana development playbook covering wallet connection, Anchor/Pinocchio programs, Codama client generation, LiteSVM/Mollusk/Surfpool testing, and security checklists. Integrates with the Solana MCP server for live documentation search. Prefers framework-kit (@solana/client + @solana/react-hooks) for UI, wallet-standard-first connection (incl. ConnectorKit), @solana/kit for client/RPC code, and @solana/web3-compat for legacy boundaries.

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Self-test both Telegram rails on this machine, the MCP connector and the userbot library, with a deterministic zero-token detector plus a real in-session MCP probe, and print a per-rail verdict with the exact fix for whichever is down. Triggers: "/tg-check", "are both tg rails up", "check telegram channels".

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。

Publish a vetted post to one of your own Telegram channels or supergroups over the MCP connector rather than a browser, with the channel resolved strictly by id from a registry, rate-guarded and draft-first. It never posts to a chat matched by name similarity. Triggers: "/tg-post", "publish to the telegram channel".

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Health-check the connected MCP servers and scout new ones: the safe pre-flight before integration work, plus a connector finder. Read-only by default. Triggers: "/mcp", "/mcp health", "/mcp discover <need>", "which MCP servers are alive", "find an MCP for <X>".

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。

Check, search or digest Gmail across several mailboxes over the owner's own OAuth connector, with no browser and near-zero tokens for the raw pull. Read-only by default: drafting and sending go through the outbound approval gate. Triggers: "/gmail", "check mail", "any important emails", "find the email about <X>".

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。

Recover a session after a hard crash (app died, machine rebooted, context lost mid-work): replay the turn-state ledger for the last requests, files and decisions, run a green/red health ping over the system map, file sync and MCP connectors, then rebuild the previous session history for pickup. Triggers: "/1", "resume after crash", "wake".

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Use when the user asks to "track our share of voice", "what share of the conversation do we own vs competitors", or "trend our SOV this quarter"; computes SOV% = brand mentions ÷ (brand + competitor panel mentions) per platform per period on a LOCKED competitor panel — a panel switch invalidates the trend (restart the series and log the break; the ECHO O3 rule) — plus a sentiment-weighted SOV variant (sentiment labeled Estimated unless human-coded) and a Wikipedia-pageviews attention-share alternative; built from keyless listening connectors, gdelt.py news echo, and user exports — public counts only, closed platforms are never scraped. Not for backlink or offsite SEO signals — use offsite-signal-analyzer. 声量份额/竞品声量对比/提及份额/注意力份额

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Analyze Profound AI-visibility and citation-tracking data when an authorized connector is available. Use for time-series brand mentions, cited prompts, competitor co-mentions, and AI-answer visibility trends.

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Analyze SE Ranking organic and AI-visibility data when an authorized connector is available. Use for rankings, competitors, backlinks, SERP features, and cross-platform AI share-of-voice evidence.

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。

Crawl, map, or scrape websites with Firecrawl when an authorized connector is available. Use for JavaScript-rendered pages, site inventories, broken-link discovery, and bounded multi-page SEO collection.

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Analyze live Ahrefs backlink, referring-domain, organic-keyword, and content data when an authorized Ahrefs connector is available. Use for Ahrefs-specific SEO evidence, not for estimates when no live connection exists.

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Search and analyze Estuary task logs with jq filtering. Use when investigating task failures, debugging connector errors, analyzing behavior patterns, or streaming live logs. Use when user says "check logs", "show me logs", "task failing", "why is my capture failing", "why is my materialization failing", "error messages", "why did it fail", "search task logs", "shard failed", "follow logs", "increase log level", "debug logging", "is this log message normal", "what does this message mean", "connection timeout", or "i/o timeout".

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 when working with Airbyte — airbyte data integration platform management. Covers connection status monitoring, sync job tracking, source and destination health, schema change detection, workspace management, and connector upgrades. Use when checking sync status, investigating job failures, managing Airbyte connections, or auditing data pipeline configurations.

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 when working with Activemq — activeMQ broker health, destination management, advisory topic monitoring, network connector status, and message flow analysis.

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 when working with Aws App Runner — aWS App Runner service management and health analysis. Covers service inventory, deployment status, auto-scaling configurations, custom domain associations, VPC connector settings, and observability configurations. Use when inspecting App Runner services, debugging deployment failures, reviewing scaling behavior, or auditing service configurations.

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Use when working with Gcp Idle Resources — detect unused and idle GCP resources that incur cost without providing value. Covers unattached Persistent Disks, unused external IPs, stopped VMs, idle Cloud NAT, idle load balancers, old snapshots, idle Cloud SQL instances, abandoned GKE node pools, unused VPC connectors, and orphaned Filestore instances. Includes estimated monthly waste per resource and anti-hallucination rules for safe detection.

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Use when working with Azure Logic Apps — azure Logic Apps workflow run analysis, trigger history, connector management, error diagnostics, and workflow definition inspection via Azure CLI.

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Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude do", "teach me", "learn to use"; questions about artifacts, projects, skills, plugins, connectors, MCP; requests about rolling Claude out to a team, class, or organization; and any ask for training materials, onboarding content, or learning resources. Use it when the user is learning how to use a feature or product — not when they are mid-task and just want the task done. This skill composes with other skills: after consulting product documentation to answer how a Claude feature works, also check here for a matching course or tutorial — a docs-grounded answer and an Academy recommendation belong together. Only recommend on a strong match; never invent Academy content.

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Control local apps through Computer Use (the @oai/sky runtime) inside the Codex app. Use when the session uses a custom (non-OpenAI) model, for example deepseek-v4-flash or mimo-v2.5, and the user asks to control the computer, operate a desktop app's UI, use Safari or Chrome through computer use, click or type in an app, or take a screenshot of an app. Prefer purpose-built connectors, APIs, or CLIs when they exist.

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。