「agent-skills」の検索結果

Create a materialization for any Estuary destination connector. Use this generic skill when no dedicated skill exists for the target system. Use when user says "materialize to", "send data to", "destination connector", or "set up materialization".

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。

Create a HubSpot materialization to write Estuary collections back into HubSpot CRM objects (Contacts, Companies, Deals, Tickets, etc). Use when setting up HubSpot as a destination for captured data. Use when user says "send to HubSpot", "materialize to HubSpot", "write back to HubSpot", or "HubSpot destination".

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。

Diagnose and fix SSH tunnel connection issues for Estuary captures and materializations. Use when seeing tunnel failures, connection timeouts, or permission denied errors. Use when user says "SSH tunnel failed", "connection timeout via tunnel", "permission denied SSH", "tunnel not working", "network-tunnel failed", "no pubkey loaded", "bastion host not connecting", or "RSA key format".

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。

Create an Estuary derivation for stateless filtering, field selection, and per-document field transformation. Use for WHERE clauses, projecting fields, computing new fields from existing ones, or data cleansing. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this (renaming alone is usually a projection, not a derivation). Use when user says "filter-transform derivation", "derivation to filter by status", "transformation with WHERE clause", "derive computed fields", "cleanse data with a derivation", or "stateless derivation".

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。

Create an HTTP Ingest (webhook) capture to receive data via HTTP POST requests. Use when setting up webhooks from GitHub, Shopify, Stripe, or any JSON source. Use when user says "set up webhook capture", "HTTP ingest to Estuary", "receive POST requests to Estuary", or "webhook capture".

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。

Create a PostgreSQL materialization to stream Estuary collections into PostgreSQL tables. Use when setting up PostgreSQL as a destination for captured data. Use when user says "send to Postgres", "materialize to PostgreSQL", "Postgres destination", or "load into Postgres".

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。

Create an Estuary derivation that maintains a sliding time window of events (e.g. "transfers in the last 24h", "failed logins in the last 5 minutes") using internal SQLite state and readDelay for time-based expiration. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this. Use when user says "windowing derivation", "derivation for last-24h events", "rolling-window derivation", "sliding-window transformation", "fraud-detection derivation", "rate-limit derivation", or "time-window derivation".

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。

Create an Estuary derivation with custom SQLite state (internal tables) to make per-document decisions based on accumulated history — account balances, inventory levels, approval workflows, deduplication. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this. Use when user says "stateful derivation", "derivation to track balance", "transformation to approve based on state", "derive an approval workflow", "deduplication derivation", or "build a stateful derivation".

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。

Create a Redshift materialization to stream Estuary collections into Amazon Redshift tables. Use when setting up Redshift as a destination for captured data. Use when user says "send to Redshift", "materialize to Redshift", "Redshift destination", or "load into Redshift".

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。

Write Estuary derivations in Python — async-generator transforms, Pydantic-typed source/output, optional persistent state, and dependency installation via uv. Use for ML/embeddings, async API calls, or any transform where SQL and TypeScript are awkward. Derivations add complexity and cost (and Python derivations require a private/BYOC data plane) — confirm the user wants a Python derivation before reaching for this. Use when user says "python derivation", "write a derivation in python", "embed with a python derivation", "ML derivation", "call an API from a derivation", or anything mentioning model2vec / huggingface / pydantic in a derivation 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。

Create an Alpaca capture using flowctl to stream stock trade data into Estuary collections. Use when setting up an Alpaca Market Data source for historical and real-time stock trades. Use when user says "capture Alpaca", "stream stock trades", "Alpaca market data", or "connect Alpaca to Estuary".

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。

Create an Estuary derivation that joins two or more collections on a shared key, merging their fields into a single enriched collection. Use for data enrichment, denormalisation, building wide tables for BI, and real-time CDC joins. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this (a destination-side SQL join or BI tool view is often simpler). Use when user says "join-collections derivation", "derivation to join two collections", "transformation to enrich with customer data", "derive a wide table", "lookup-join derivation", or "build a join derivation".

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。

Pause and restart Estuary connectors by disabling and re-enabling shards via flowctl. Use when temporarily stopping a connector, performing source/destination maintenance, or forcing a fresh restart to clear transient errors or load updated configs immediately. Use when user says "pause connector", "stop connector", "restart connector", "disable connector", "enable connector", "re-enable task", "disable shards", "stop my capture", "stop my materialization", "disable my materialization", "force restart connector", "connector maintenance", "temporarily stop processing", "shards disable true", "enable shards", "resume connector", or "unpause connector".

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。

Create a ClickHouse materialization to stream Estuary collections into ClickHouse tables. Use when setting up ClickHouse as a destination for captured data. Use when user says "send to ClickHouse", "materialize to ClickHouse", "ClickHouse destination", or "load into ClickHouse".

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。

Structured code review through the shared OpenClaw agent-skills installation.

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。

Find and rank influencers by niche, engagement, and authenticity using Xpoz. Searches Twitter, Instagram, and Reddit for active voices in any topic. Use when asked to "find influencers", "discover thought leaders", "who's talking about X", "influencer research", or "find KOLs".

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 and analyze Reddit discussions for market research, product feedback, and community insights using Xpoz. Use when asked to "search Reddit", "what does Reddit think about X", "Reddit feedback on X", "subreddit analysis", or "Reddit market research".

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。

Export Twitter/X data to CSV for analysis using Xpoz. Search by keywords, author, date range, and download complete datasets (up to 500K rows). Use when asked to "export tweets", "download Twitter data", "get tweets as CSV", "Twitter dataset", or "bulk tweet download".

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 brand or topic sentiment across Twitter, Reddit, and Instagram using Xpoz. Classifies posts as positive/neutral/negative, extracts recurring themes, and generates a sentiment report. Use when asked for "sentiment analysis", "what are people saying about X", "brand sentiment", or "social media opinion on 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。

Monitor social platforms for security threats, vulnerability discussions, and breach intelligence using Xpoz. Use when asked to "find CVE discussions", "security threat monitoring", "OSINT social media", "vulnerability intelligence", "breach mentions", or "threat intel from Twitter/Reddit".

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。

Compare brands and products across social media — share of voice, sentiment, positioning, and audience overlap using Xpoz. Use when asked to "compare brands", "competitive analysis", "share of voice", "brand vs brand", or "competitive intelligence".

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。

GitHub Issue群からClaude Code並列開発用の実行プロンプト集（docs/prompts/xxx.md）を自動生成するスキル。 「開発計画を作成して」「実行プロンプトを生成して」「dev-planを作って」「プロンプト集を作って」 「並列開発の計画を立てて」などのリクエストで発動。 Issue番号リストを受け取り、依存関係のWave構造を対話で決定し、 /gtr-workflow → 実装 → /e2e-test → /pull-request の一連の指示を各Issueごとに生成する。

Git Worktree Runner (gtr) workflow guidance for parallel development with Claude Code. Use when the user asks about git worktrees, parallel AI development, running multiple Claude sessions, managing worktrees with gtr, or setting up isolated development environments for feature work.

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。

プルリクエスト作成。コミット済みの変更内容を分析し、簡潔でわかりやすいPR内容を自動生成。 「PRを作成して」「プルリクエストを作って」「PRお願い」などのリクエストで発動。