260 skills · sorted by relevance
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", "TextAnalyticsClient".
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Determines when and how revenue is recognized — performance obligations, contract terms that change the answer, and the deal structures that create accounting problems. Use this to work out how a contract should be recognized, review a non-standard deal before it is signed, understand deferred revenue, or spot terms that would delay or reverse recognition.
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PaddleOCR text recognition skill using PP-OCRv5 lightweight model. Supports natural scene and complex document text detection and recognition. Use when user needs OCR text extraction from images.
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Extract a license plate number from an image URL using the CarsXE Plate Recognition API. Use this when a user shares a photo of a vehicle or license plate and wants to identify the plate number.
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Operate ASRT SpeechRecognition Chinese ASR data, acoustic models, pinyin language model, and serving clients.
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Automates invoice generation, billing workflows, payment tracking, and revenue recognition for SaaS and service businesses. Use when building billing pipelines, generating invoice PDFs, usage-based invoicing, subscription management, payment reminders, or financial reporting. Trigger words: invoice, billing, payment, subscription, usage billing, revenue recognition, accounts receivable, dunning, proration, Stripe billing, generate invoice, create bill.
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Recognize and extract text from scanned PDFs and images with ComPDF OCR workflows. Use for OCR, searchable PDF generation, text recognition, table recognition, and scanned-document extraction requests.
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Aural skills development covering interval recognition, chord quality identification, rhythmic and melodic dictation, sight-singing, and progressive pedagogy. Covers the Kodaly method (hand signs, relative solmization, singing-first approach), interval identification strategies, chord quality and inversion recognition, harmonic dictation, solfege systems (fixed-do vs. movable-do), Gordon's Music Learning Theory, Suzuki method principles, and structured difficulty sequencing. Use when developing listening skills, practicing dictation, preparing sight-singing, or designing ear training curricula.
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Recognize and locate instances of an object in an image with a local vision LLM. Wraps kuzco's tool_llm_image_recognition() ellmer tool. Use when the task needs finding, counting, or locating specific objects (faces, cars, animals) in an image.
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Generate MaaFramework Pipeline nodes and recognition snippets from screenshots or observed UI state. Use for OCR node generation, ROI sweep, choosing TemplateMatch/OCR/ColorMatch/CustomRecognition, preserving target-file schema style, and designing `next`/`[JumpBack]` links before merging generated nodes into pipeline JSON.
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Guide a person in systematic observation of systems, patterns, or phenomena. AI coaches neutral attention, field notes methodology, pattern recognition, hypothesis formation, and structured reporting for debugging, research, and system understanding. Use when a person wants to understand a system's behavior before intervening, when someone keeps jumping to conclusions and needs the discipline of observation first, when preparing an evidence-based report, or when studying team dynamics or process effectiveness through direct observation.
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Sustained neutral pattern recognition across systems without urgency or intervention. Maps naturalist field study methodology to AI reasoning: framing the observation target, witnessing with sustained attention, recording patterns, categorizing findings, generating hypotheses, and archiving a pattern library for future reference. Use when a system's behavior is unclear and action would be premature, when debugging an unknown root cause, when a codebase change needs its effects witnessed before further changes, or when auditing own reasoning patterns for biases or recurring errors.
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Naturalistic decision-making research showing how experts make decisions through recognition-primed processes
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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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Spot patterns appearing in 3+ domains to find universal principles
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Transcribe speech to text using the Speech framework. Use when implementing live microphone transcription with AVAudioEngine, recognizing pre-recorded audio files, configuring on-device vs server-based recognition, handling authorization flows, or adopting the new SpeechAnalyzer API (iOS 26+) for modern async/await speech-to-text.
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OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.
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OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.
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Support product returns from eligibility checks and inspection to refunds and decisions about resale, repair, or disposal. The skill also provides frameworks for reviewing fraud indicators, handling warranty claims, and recovering costs from suppliers.
Design and generate simple, cute mascot images for products, brands, or communities, aiming for recognition at 32 × 32 pixels. Explore distinct concepts and color choices through separately generated square candidates with labeled design details.
Build agent memory with ReasoningBank and AgentDB. Record actions and outcomes, retrieve similar experiences, assess results, and consolidate memories into reusable patterns so agents can draw on past work when making decisions.
Implement agents that use recorded task outcomes to choose future approaches. ReasoningBank supports matching past patterns, comparing strategies, retaining experience in AgentDB, and tracking how strategy success and learning change over time.
Read local PDFs, scanned images, and Office documents for summaries, questions, and citations. Extract readable content, search indexed documents, and work through long files in sections while retaining precise page and block references.
Build agent memory with ReasoningBank and AgentDB. Record actions and outcomes, retrieve similar experiences, assess results, and consolidate memories into reusable patterns so agents can draw on past work when making decisions.