「processing」の検索結果

[Document Processing] Use when you need to convert PDF files to Markdown with support for native text PDFs and scanned documents (OCR).

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[Document Processing] Use when you need to convert markdown files to PDF with syntax highlighting and custom CSS support.

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。

[Document Processing] Use when you need to convert Microsoft Word ( DOCX) files to Markdown with GFM support (tables, images, code blocks).

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。

Remove Gemini AI watermarks from images using GeminiWatermarkTool (GWT). Use this skill whenever the user mentions: Gemini watermark, 浮水印, AI image cleanup, removing logos from Gemini-generated images, Google ImageFX cleanup, batch processing AI-generated photos, or anything about a semi-transparent logo in the bottom-right corner of an image — even if they don't say "GeminiWatermarkTool" explicitly. Also trigger for follow-up requests like "the corner still looks dirty" or "there's still residual artifacts" after a previous removal attempt.

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。

Lark/Feishu real-time event listening / subscribing / consuming: stream events as NDJSON via `lark-cli event consume <EventKey>` (covers IM message receive, reactions, chat member changes, etc.). Use for Lark bots, real-time message processing, long-running subscribers, streaming webhook/push handlers. Supports `--max-events` / `--timeout` bounded runs and a stderr ready-marker contract — designed for AI agents running as subprocesses.

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Create aesthetically beautiful interfaces following proven design principles. Use when building UI/UX, analyzing designs from inspiration sites, generating design images with ai-multimodal, implementing visual hierarchy and color theory, adding micro-interactions, or creating design documentation. Includes workflows for capturing and analyzing inspiration screenshots with chrome-devtools and ai-multimodal, iterative design image generation until aesthetic standards are met, and comprehensive design system guidance covering BEAUTIFUL (aesthetic principles), RIGHT (functionality/accessibility), SATISFYING (micro-interactions), and PEAK (storytelling) stages. Integrates with chrome-devtools, ai-multimodal, media-processing, ui-styling, and web-frameworks skills.

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Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text. Triggers: "text analytics", "sentiment analysis", "entity recognition", "key phrase", "PII detection", "TextAnalyticsClien...

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Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models. Use for invoice processing, receipt extraction, ID document analysis, and custom document models. Triggers: "Document Intelligence", "DocumentIntelligenceClient"...

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Extract text, tables, and structured data from documents using Azure Document Intelligence (@azure-rest/ai-document-intelligence). Use when processing invoices, receipts, IDs, forms, or building custom document models.

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Automate AWS GuardDuty threat detection findings processing using EventBridge and Lambda to enable real-time incident response, automatic quarantine of compromised resources, and security notification workflows.

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Build effective detection rules using Splunk Search Processing Language (SPL) correlation searches to identify security threats in SOC environments.

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Leverages Splunk Enterprise Security and SPL (Search Processing Language) to investigate security incidents through log correlation, timeline reconstruction, and anomaly detection. Covers Windows event logs, firewall logs, proxy logs, and authentication data analysis. Activates for requests involving Splunk investigation, SPL queries, SIEM log analysis, security event correlation, or log-based incident investigation.

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Execute the implementation plan by processing and executing all tasks defined in tasks.md

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Convert PDF documents to clean structured Markdown for LLM context. Supports two modes: fast (PyMuPDF) and accurate (IBM Docling TableFormer AI). Features aggressive persistent caching, image extraction with metadata, table detection, and batch processing. Use when asked to convert PDFs, extract PDF content, parse documents, or prepare PDF data for AI/LLM consumption.

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Unified document optimization skill that chains docling-converter, imagemagick-expert, and markdown-to-pdf. Automatically detects input format, applies appropriate conversion pipeline, optimizes embedded images, and produces web/print-ready output with configurable quality presets. Use when converting documents through multi-step pipelines, optimizing PDF images, creating print-ready documents from various sources, or batch processing documents with image optimization.

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Work the prototyping lab itself — where runs live, what a run is, how to promote a run into the checked example library, and how to add a new runtime (Processing in Rust, Cinder) in one module. Use when asked to add a language or framework to the lab, to turn a prototype into a reusable example, to find or tidy what is in the lab, or when the lab's folder or catalog needs explaining.

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Split documents into overlapping token chunks for RAG pipelines and LLM context windows. Zero dependencies.

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Proposes redactions of personal identifiers in pasted text or an attached document (names, contact details, identification and account numbers, dates that identify, quasi-identifiers) and returns a DRAFT redacted copy with consistent placeholder tokens plus a redaction table stating what was replaced, where and why, with a confidence level and a blank reviewer decision per row. Use when the user asks to "redact the names in this document", "de-identify this transcript before we share it", "strip personal data from these notes", "anonymise this report for publication" or "what would need redacting here". Do not use for assessing a planned processing activity, use dpia-draft-pack instead; do not use for working out what data an incident exposed, use data-incident-impact-brief instead. Never declares a document anonymised, safe to release or compliant. Drafts for human review; never approves, authorises or signs off.

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Handle UTF-8 and text encoding safely in WordPress plugins, especially on WP 6.9+ where wp_is_valid_utf8(), wp_scrub_utf8(), and noncharacter helpers replace older seems_utf8-style checks. Covers when to validate, scrub, reject, or preserve invalid bytes; wp_check_invalid_utf8 behavior; XML/JSON/feed/export boundaries; and avoiding data loss from premature replacement. Use when processing imported text, CSV, XML, feeds, email, REST payloads, AI prompts, logs, filenames, or external API data.

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Optimize images for web performance — format conversion (WebP, AVIF), responsive sizing, compression, background removal, lazy loading, and WordPress media library integration. Uses MCP bridge tools (resize_image, remove_background) as primary; the Design Stack media worker (Sharp) as fallback for advanced/batch processing. Use when you need to resize images for social media, convert formats for faster page loads, remove backgrounds from product photos, generate alt text, or batch-process an entire media library.

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Apply when designing commands, lifecycle steps, or processing loops that run amid crashes, restarts, and retries. Converge to the same end state regardless of partial prior runs.

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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".

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Small-business bookkeeping skills for converting financial evidence into accountant-reviewable outputs, including setup/context, receipt processing, expense categorization, bank reconciliation, tax preparation, monthly close, jurisdiction-aware tax references, plus specialized skills for home office, vehicle, meals, depreciation, 1099 contractors, and estimated taxes. Trigger on "help me with my bookkeeping", "set up my bookkeeping", "bookkeeping context", "chart of accounts", "process my receipts", "categorize expenses", "reconcile my bank statement", "get my books ready for taxes", "close the month", "organize my finances".

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Extract structured data from receipts and invoices for bookkeeping, expense tracking, and tax preparation. Supports email, photos, scanned images, PDFs, and accounting exports. Outputs vendor, date, amount, tax, line items as table, CSV, or JSON. Trigger on "process receipts", "extract receipts from email", "scan invoices", "capture expenses".

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。