「rds」の検索結果

Import data into the AWS data lake from S3 files, local uploads, JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS, Aurora), Amazon Redshift, Snowflake, BigQuery, DynamoDB, or existing Glue catalog tables (migration). Default target is S3 Tables; standard Iceberg on a general purpose bucket is supported where S3 Tables is not adopted. Handles one-time loads, recurring pipelines, migrations. Triggers on: import data, load data, ingest, sync database, migrate table, move data to AWS, set up pipeline, ETL, pull from Snowflake, query BigQuery into S3, export DynamoDB, CTAS, convert to Iceberg. Do NOT use for setting up or troubleshooting Glue connections (use connecting-to-data-source), creating empty tables (use creating-data-lake-table), running queries (use querying-data-lake), finding tables by fuzzy name (use finding-data-lake-assets), catalog audit (use exploring-data-catalog), or SaaS platforms like Salesforce, ServiceNow, SAP, MongoDB, Kafka.

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Auto-activate CCS CLI delegation for deterministic tasks. Parses user input, auto-selects optimal profile (glm/kimi/custom) from ~/.ccs/config.json, enhances prompts with context, executes via `ccs {profile} -p "task"` or `ccs {profile}:continue`, and reports results. Triggers on "use ccs [task]" patterns, typo/test/refactor keywords. Excludes complex architecture, security-critical code, performance optimization, breaking changes.

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Apply production-ready Apollo.io SDK patterns. Use when implementing Apollo integrations, refactoring API usage, or establishing team coding standards. Trigger with phrases like "apollo sdk patterns", "apollo best practices", "apollo code patterns", "idiomatic apollo", "apollo client wrapper".

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Apply production-ready patterns for the Anima SDK design-to-code pipeline. Use when building reusable Anima client wrappers, implementing output caching, or establishing team standards for design-to-code automation. Trigger with: "anima SDK patterns", "anima best practices", "anima code patterns".

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Build a reliable Algolia indexing pipeline for full replacements, incremental updates, settings, synonyms, and rules. Use when a source of truth must publish deterministic search state. Trigger with "Algolia indexing workflow", "replace index records", or "sync Algolia".

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Instrument an Algolia integration for actionable availability, latency, freshness, relevance, and event-health signals. Use when defining dashboards, alerts, traces, or service objectives. Trigger with "monitor Algolia", "Algolia metrics", or "search observability".

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Design and audit the data lifecycle for records and user events sent to Algolia. Use when minimizing indexed fields, handling deletion requests, or documenting retention and privacy boundaries. Trigger with "Algolia privacy", "delete Algolia user data", or "index data review".

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Rigorous, defensible email-spoofability verdict and SPF supply-chain risk analysis computed from published DNS alone. Deepens the record-level SPF/DMARC/DKIM/BIMI/MTA-STS/DNSSEC fetch recipes in the offensive-osint arsenal (§16.14) with the reasoning that section doesn't do: a priority-ordered composite verdict for whether an attacker can actually land header-From-spoofed mail in an inbox, and by which vector (exact-domain vs subdomain) — grounded in the single most-misunderstood distinction in email security: the envelope MAIL FROM that SPF authenticates vs the visible header From: that only DMARC governs. Explains precisely why SPF -all/~all alone is NOT spoof-proof without DMARC enforcement, and why SPF +all bypasses DMARC even under p=reject pct=100. Covers RFC 7208 §4.6.4's 10-DNS-lookup / 2-void-lookup PermError fail-open condition with a runnable stdlib-only lookup-counter script, plus the SPF-include-takeover supply-chain vector (an attacker re-registering a dead include inherits SPF-pass authority over the victim domain) with strict transient-vs-NXDOMAIN discrimination discipline so a temporary SERVFAIL is never mistaken for a takeover lead. Fully passive: DNS TXT reads only, no mail sent, no RCPT TO probe, no API keys. Use when auditing a domain's real spoofing resistance (not just its published records), explaining to a client why 'we have SPF -all' does not mean they're covered, investigating an SPF PermError or an unusually long include chain, evaluating a dead SPF include as a takeover lead, or writing a defensible spoofability finding for a deliverable.

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Advanced TypeScript patterns including generics, conditional types, mapped types, template literals, and type guards

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Monitoring and observability with OpenTelemetry, Prometheus, Grafana dashboards, and structured logging

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Apply when wiring validation, error handling, or framework adapters. Concentrate guards at system boundaries (CLI, config, network, external APIs); trust internal types and keep business logic in pure functions.

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Pre-PR discipline for a public-by-default repo. What a reviewer enforces beyond CI: secrets and internal data in diffs or screenshots, docs that name their reader, and the cleaning pass where incomplete or confusing artifacts get dropped. Use before opening any PR against `gridaco/grida` or when finalizing work for review.

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SEO best practices for the Grida project across Next.js pages, blog posts, and documentation. Covers Next.js metadata API, Open Graph / Twitter cards, sitemaps, image search optimization, structured data (JSON-LD), Docusaurus frontmatter, and content writing for search. Use when creating or editing public-facing pages under editor/app/(www), writing blog posts, authoring docs, or reviewing SEO-related metadata. Trigger phrases: "SEO", "metadata", "sitemap", "open graph", "og image", "meta tags", "search ranking", "structured data", "JSON-LD".

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Inflate skill discovery through repeated activation keywords

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Use when the user mentions Jira issues (e.g., "PROJ-123"), asks about tickets, wants to create/view/update issues, check sprint status, or manage their Jira workflow. Triggers on keywords like "jira", "issue", "ticket", "sprint", "backlog", or issue key patterns.

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Converts OpenAPI 3.0 JSON/YAML to TypeScript interfaces and type guards. This skill should be used when the user asks to generate types from OpenAPI, convert schema to TS, create API interfaces, or generate TypeScript types from an API specification.

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Datadog CLI for searching logs, querying metrics, tracing requests, and managing dashboards. Use this when debugging production issues or working with Datadog observability.

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Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases. Credits: Original skill by @blader - https://github.com/blader/humanizer

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Subdomain takeover detection and exploitation playbook. Use when targets have dangling CNAME/NS/MX records pointing to deprovisioned cloud resources, expired third-party services, or unclaimed SaaS tenants that an attacker can register to serve content under the victim's domain.

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Review designs, products, and features with Steve Jobs' standards: ruthless simplicity, focus, and end-to-end excellence. Use when the user mentions "Steve Jobs review", "design review", "product review", "what would Steve do", "insanely great", "this feels too complicated", "too many features", "product taste", "saying no", or "is this good enough to ship". Also trigger when critiquing a UI, feature, or roadmap for focus and simplicity, cutting scope to the essential, or pressure-testing the whole experience from first run to daily use. Covers the simplicity audit, the no list, design-is-how-it-works, end-to-end ownership, demo culture, and a Jobs-style review protocol with binary verdicts. For visual design fundamentals, see refactoring-ui. For usability audits, see ux-heuristics. For detail polish, see microinteractions.

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Apply named refactoring transformations to improve code structure without changing behavior. Use when the user mentions "refactor this", "code smells", "extract method", "replace conditional", "technical debt", "move method", "inline variable", "decompose conditional", or "clean up this messy code". Also trigger when cleaning up legacy code, preparing code for new features by restructuring, or identifying which transformation fits a specific code smell. Covers smell-driven refactoring, safe transformation sequences, and testing guards. For code-quality foundations, see clean-code. For managing complexity, see software-design-philosophy.

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Design motivation systems using Autonomy, Mastery, and Purpose (AMP) for products and teams. Use when the user mentions "intrinsic motivation", "gamification isnt working", "rewards arent working", "autonomy", "mastery", "purpose-driven", "my team is disengaged", or "how do I motivate people". Also trigger when designing onboarding progression, fixing broken gamification, or building team structures that sustain high performance. Covers why carrot-and-stick fails and how to build progress systems. For habit-forming product loops, see hooked-ux. For retention behavior design, see improve-retention.

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Diagnose and fix retention problems using behavior design (B=MAP). Use when the user mentions "users sign up but dont stick around", "activation rate", "onboarding friction", "retention metrics", "why users dont complete", "churn analysis", or "aha moment". Also trigger when analyzing cohort retention curves, designing activation milestones, reducing time-to-value for new users, or investigating why users quit after their first session. Covers the Ability Chain, prompt design, and tiny behaviors that compound. For habit loops and variable rewards, see hooked-ux. For intrinsic motivation, see drive-motivation.

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Use when a video/audio task needs OpenChatCut transcription, captions, subtitles, subtitle styling, transcript search, transcript readiness checks, or enabling captions, including local or attached videos where the user asks to add captions/subtitles, transcribe, create bilingual subtitles, clean talking-head speech, remove filler words, or trim pauses.

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。