'batch' 검색 결과

Detects AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing rate) and classifying samples with machine learning models. Supports batch analysis of audio files, generates confidence scores, and produces forensic reports. Activates for requests involving deepfake voice detection, vishing investigation, AI-generated speech analysis, voice cloning detection, or audio authenticity verification.

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Solana development patterns used in the Pump SDK — Anchor IDL-based program interaction, SPL Token and Token-2022 management, transaction construction with instruction composition, RPC batching, and cross-program coordination.

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Production-quality Bash scripts for Solana vanity generation, keypair verification, batch operations, dependency auditing, and test orchestration — with security-hardened patterns including file permissions, input validation, and cleanup traps.

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Batch-generate images via OpenAI Images API. Random prompt sampler + `index.html` gallery.

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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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Builds DRAFT user personas from the research notes, interview summaries, survey free text and support themes the user provides: for each persona the goals, pains, jobs to be done, context of use, quotes exactly as supplied with their participant codes, and the evidence count behind every attribute, with names, demographics and any detail no participant stated left UNKNOWN rather than invented. Use when the user asks to "build personas from these interviews", "who are our users based on this research", "draft user personas", "turn these research notes into personas" or "update our personas with the new interviews". Do not use for theming a batch of customer feedback into counts, use customer-feedback-theme-synthesis instead; for exit interviews, use exit-interview-synthesis; for the requirements those personas imply, use product-requirements-draft. Drafts for human review; never approves, authorises or signs off.

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Synthesises a batch of customer feedback (survey answers, reviews, ticket and chat comments) into a DRAFT themed report: coded themes with record counts and shares, anonymised verbatim quotes cited to record codes, contradictions and unverified claims, and the follow-up questions to answer next. Produces no sentiment score or percentage positive as fact; ratings appear only as distributions with n. Use when the user asks to "theme this feedback", "what are customers saying", "summarise these survey answers", "analyse these reviews", "find the top complaints in these comments" or "code this voice of the customer data". Do not use for exit interviews, use exit-interview-synthesis instead; for sorting a live queue and drafting replies, use ticket-triage-pack; for project retrospectives, use lessons-learned-synthesis. Drafts for human review; never approves, authorises or signs off.

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Turns one long support ticket thread (helpdesk history, email chain, chat transcript, call notes) into a one-page DRAFT escalation summary: the customer's ask in their own words, account context as stated, a dated history, what was tried and the stated result of each attempt, the current state, and what is needed from whom by when, every line referenced to a message and every missing fact marked UNKNOWN. Use when the user asks to "escalate this ticket", "summarise this thread for tier two", "write the hand-over for this case", "what has been tried so far", "brief engineering on this customer issue" or "prepare the escalation note". Do not use for a batch of tickets, use ticket-triage-pack instead; for the review after an outage, use incident-postmortem-drafter. Drafts for human review; never approves, authorises or signs off.

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Triages a batch of customer support tickets (helpdesk export, shared mailbox, chat transcripts, web forms) into one row per ticket with category, urgency graded on the evidence in the ticket, suggested next action and owner, plus a DRAFT customer reply for every ticket that needs one, returned as one Markdown pack. Use when the user asks to "triage these tickets", "sort the support queue", "what needs an answer first", "categorise this backlog", "draft replies for these tickets" or "build today's queue review". Do not use for internal requests from colleagues, use request-intake-triage instead; for one long thread that needs handing over, use escalation-summary; for a personal mailbox, use inbox-triage. Drafts for human review; never approves, authorises or signs off.

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Eat the elephant one bite at a time: turn a large list-shaped job into a finite routine that chews a small batch every night, detects when it is done, switches itself off and reports. Triggers: /elephant, eat the elephant, split into bites, make it a routine, ten a day, backfill everything.

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Find the canonical Rosetta Stone attribute that best matches a fuzzy description, semantic phrase, or required schema shape. Searches the catalog with pagination, describes the shortlist in one batched call, ranks candidates by name + shape match, and returns the canonical attribute ID plus close alternatives. Use when: "find the X attribute", "what's the graph-edge attribute ID", "look up the email Rosetta Stone attribute", "search the attribute catalog for Y", "which attribute has SOURCE_ID + TARGET_ID + IS_DIRECTED". (narrative-common)

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Repair confirmed architecture drift in small batches while preserving public canon and avoiding broad opportunistic refactors.

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General Blender workflow skill for AI agents working with .blend, .fbx, .obj, .glb, glTF, materials, scene inspection, bpy automation, headless Blender batch runs, export/reimport validation, previews, and optional Blender MCP control. Use when a task asks to open, inspect, create, automate, convert, optimize, render, or verify Blender or 3D asset files in a user-agnostic way.

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Match book entries against bank or credit card statements to find discrepancies, missing transactions, and duplicates. Uses exact, near, and batch matching with balance verification. Trigger on "reconcile bank statement", "match transactions", "bank balance doesn't match", "close the books".

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Orchestrate HITL triage of review findings using parallel agents. Use when the user says 'triage these findings' or 'run findings triage' or has a batch of review findings to process.

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Batch-commit all uncommitted changes grouped by relevance. Use when multiple accumulated changes need committing. Invoked by saying "commit all" or "commit everything".

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Document completed work — update task log, sync documentation, log observations. Use after finishing a task or batch of changes.

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Google Sheets skill for reading and writing spreadsheets via the gws CLI. Covers cell reads, row appends, batch updates, sheet management, and formula evaluation.

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Google Docs skill for creating, reading, and updating documents via the gws CLI. Covers document creation, content retrieval, batch updates, and sharing.

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Produces structured content calendars with platform-specific posting schedules, content pillars, and batch publishing plans. Use when the task asks to "plan content", "schedule posts", "create a content calendar", "editorial calendar", "posting schedule", or "content strategy". Covers content pillars, posting cadence, multi-site calendars, seasonal hooks, and content repurposing matrices.

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Design and interpret TypeSafe Jev decision requests in NV oOS — typed choice/score/noul questions, batching, confidence thresholds, composite scoring, and guardrails. Use when classifying, routing, scoring, or safety-screening content with the typesafe_decide or typesafe_guardrail tools.

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Generate images using AI models — Gemini, DALL·E, Stable Diffusion, Midjourney, Flux, Leonardo, Ideogram, and more. MCP bridge tools are primary; the Design Stack media worker is the fallback for advanced providers. Covers prompt engineering, model selection, size/aspect ratios, style parameters, batch generation, multi-site awareness, and WordPress integration. Use when you need to create hero images, social graphics, product mockups, brand illustrations, or any visual asset for marketing, social media, or e-commerce.

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Orchestrate AI/ML pipelines for data ingestion, model training, batch inference, and RAG indexing using Prefect, Airflow, or Dagster.

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Automate SEO research with Ahrefs -- analyze backlink profiles, research keywords, track domain metrics history, audit organic rankings, and perform batch URL analysis through the Composio Ahrefs inte

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