「eda」の検索結果

eBay sold-listings scraper across 8 marketplaces (ebay.com/.co.uk/.de/.fr/.it/.es/.ca/.com.au). Takes keyword plus filters (category, price range, item condition, item location, sort order, completed toggle) and returns paginated real-sale records with itemId, url, title, condition, conditionId, endedAt, soldPrice, soldCurrency, listingType (best_offer_accepted / buy_it_now / auction), isBestOfferAccepted, buyingFormat, bidCount, shipping, totalPrice, thumbnails, seller info, sellerType. Use when user mentions ebay sold, ebay sold listings, ebay sold prices, ebay completed listings, ebay comps, ebay resale prices, ebay auction sold results, ebay best offer accepted, scrape ebay sold, ebay market research, ebay pricing intelligence, ebay flipping research, real sold prices ebay, get sold prices from ebay. Also applies to price benchmarking, sold-price analytics, resale valuation, cross-marketplace price arbitrage, appraisal for collectibles, brand demand tracking on ebay.

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Build continuous-shot motion-driven HTML stories from a subject or narrative, including research, story structure, consistent AI stills, Seedance scene and connector clips, interface styling, media normalization, and browser QA. Use for immersive journeys, timelines, product stories, fictional worlds, or other scene-based visual narratives whose camera should flow from beginning to end; not for ordinary autoplay video pages or general web apps.

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Convert .NET tests from xUnit.net v2/v3 to MSTest v4 while preserving VSTest or MTP. Use for replacing xunit packages, Fact/Theory/InlineData/MemberData, assertions, IClassFixture/ICollectionFixture, ITestOutputHelper, TestContext cancellation, traits/Owner, skips, timeouts, and xUnit parallelization. Also use when a "convert xUnit to MSTest" request may already be migrated: inspect and report the no-op. Do not use for xUnit v2-to-v3, MSTest upgrades, NUnit/TUnit conversion, or runner-only VSTest-to-MTP migration.

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Create or review Blazor components (.razor files) with correct architecture. USE FOR: writing new Blazor components that do NOT involve JavaScript interop, implementing parameters and EventCallback, RenderFragment slots, component lifecycle (OnInitializedAsync, OnParametersSet), async patterns, IAsyncDisposable, CancellationToken, CSS isolation, code-behind. DO NOT USE FOR: creating new projects (use create-blazor-project), JavaScript interop or calling browser APIs from Blazor (use use-js-interop), forms and validation (use collect-user-input), prerendering issues (use support-prerendering), HTTP data fetching patterns (use fetch-and-send-data), coordinating state between unrelated components (use coordinate-components).

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Use the `quickdesign` CLI to generate AI media — UGC promo videos, image edits, product creatives, video upscales — through Seedance, Kling, Sora2, Nano Banana, and GPT Image. Invoke this skill whenever the user asks for a talking-avatar video, multi-segment ad / promo / explainer, image edit (object swap, angle change, state change), product photoshoot, or video upscale via QuickDesign.

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Econometrics skill for OLS regression and linear models. Activates when the user asks about: "run OLS", "linear regression", "ordinary least squares", "interpret regression results", "heteroskedasticity", "multicollinearity", "regression assumptions", "robust standard errors", "GLS", "WLS", "fit a regression model", "check regression diagnostics", "OLS假设", "最小二乘法", "线性回归", "回归系数", "残差检验", "异方差", "多重共线性", "普通最小二乘", "稳健标准误", "回归诊断"

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Opinionated Bayesian modeling workflow with PyMC and ArviZ. Contains critical guardrails (nutpie sampler, prior/posterior predictive checks, LOO-PIT calibration, prior sensitivity checks, 94% HDI, non-centered parameterizations, reproducible seeds) that agents won't apply unprompted — always consult before writing Bayesian model code. Trigger on: building probabilistic/Bayesian models, prior elicitation, MCMC inference, convergence diagnostics (divergences, R-hat, ESS), model comparison (LOO-CV, ELPD, stacking weights), hierarchical/multilevel models, count regressions, logistic regression with uncertainty, prior sensitivity analysis, reporting Bayesian results, or mentions of PyMC, ArviZ, InferenceData, credible intervals, posterior distributions, shrinkage, uncertainty quantification. Also trigger for model comparison, diagnosing sampling problems, choosing priors, or presenting stats to non-technical audiences.

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Comprehensive biosignal processing toolkit for analyzing physiological data including ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use this skill when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements. Applicable for heart rate variability analysis, event-related potentials, complexity measures, autonomic nervous system assessment, psychophysiology research, and multi-modal physiological signal integration.

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AI 视频生成：文生视频 / 图生视频 / 数字人首帧驱动。通过可插拔 provider（通义万相 Wan / 火山 Seedance / 快手可灵 / OpenAI 兼容）异步生成视频，用户自备 API key。当用户说 AI 视频生成、文生视频、图生视频、AI 生成视频、AI 短视频、让图片动起来、数字人视频、生成一段视频 时使用。与 video-strategy（选型/策略）、video-editing（剪辑处理）、clipify（切片）区别：本 SKILL 是从 0 用 AI 生成新视频。

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Fine-tune public CodonFM Encodon checkpoints on labeled coding-sequence or coding-variant data using LoRA, head-only, or full fine-tuning. Use when a user explicitly asks to fine-tune CodonFM or Encodon for regression or classification. Support generic public-v1 Encodon workflows only; reject Decodon, MissenseDataset, missense_synom_agg, and generation workflows.

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Diagnose a named CCB agent by combining authoritative runtime and job lineage with deep read-only pane inspection, apply bounded recovery when evidence supports it, verify the result, and request authorization before submitting a redacted GitHub issue. Use for `$ccb_diagnose agentname`, `$ccb-diagnose agentname`, or reports that a CCB agent is stuck, disconnected, not continuing, not replying, or showing provider errors.

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Update old notes with new connections. The backward pass that /reflect doesn't do. Revisit existing notes that predate newer related content, add connections, sharpen claims, consider splits. Triggers on "/reweave", "/reweave [note]", "update old notes", "backward connections", "revisit notes".

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Lookup documented AKS fixes only when the prompt includes an exact catalog signature and all of its qualifiers: VMCannotFitEphemeralOSDisk; NodePoolMcVersionIncompatible; 'NodeImageVersion is not accepted'; AKS SkuNotAvailable with size, location, and zone; ZonalAllocationFailed with insufficient zone capacity; OverconstrainedAllocationRequest with listed constraints; nested AKS vmssCSE/CSE VMExtensionError_OutboundConnFail, VMExtensionError_K8SAPIServerConnFail, or VMExtensionError_K8SAPIServerDNSLookupFail; or AllocationFailed with the full cataloged internal-error or insufficient-regional-capacity message. Never use for quota errors, code-only or bare wrappers, generic symptoms, incomplete signatures, or failures outside AKS; use aks-troubleshooting or azure-diagnostics.

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Build and deploy full-stack web and mobile apps with AWS Amplify Gen2 (TypeScript code-first). Covers auth (Cognito), data (AppSync/DynamoDB), storage (S3), functions, APIs, and AI (Amplify AI Kit with Bedrock). Supports React, Next.js, Vue, Angular, React Native, Flutter, Swift, and Android. Always use this skill for Amplify Gen2 topics — even for questions you think you know — it contains validated, version-specific patterns that prevent common mistakes. TRIGGER when: user mentions Amplify Gen2; project has amplify/ directory or amplify_outputs; code imports @aws-amplify packages; user asks about defineBackend, defineAuth, defineData, defineStorage, defineFunction, or npx ampx. SKIP: Amplify Gen1 (amplify CLI v6), standalone SAM/CDK without Amplify (use aws-serverless), direct Bedrock without Amplify AI Kit (use bedrock).

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Use when preparing your agent for production — IAM scoping, inbound auth (JWT, SigV4), secrets management, cold start optimization, session lifecycle, rate limiting, input validation, and quota guidance. Triggers on: "production checklist", "harden agent", "production ready", "secure agent", "inbound auth", "going live", "cold start optimization", "session lifecycle", "StopRuntimeSession", "quota", "throttling", "maxVms", "rate limit", "security audit of outbound API calls", "gateway target audit for production", "restrict who can call", "lock down endpoint", "only our app can call". Not for Cedar tool-restriction policies — use agents-connect. Not for quality measurement — use agents-optimize. Not for outbound credential storage or API key wiring — use agents-connect. Not for A2A agent-to-agent auth — use agents-build. Cold start observation and diagnosis (not optimization) routes to agents-debug.

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Designs a resilience program: how to structure and standardize resilience policies across an organization, team, or portfolio (tiered policy model with availability/RTO/RPO targets and DR approach selection), and how often to run resilience activities (operational cadence). Applies when the user asks how to structure policies org-wide, what tiers/targets to set, which DR approach fits a tier, or how frequently to run assessments, FIS experiments, GameDays, or autoshift practice. Does not apply to creating or configuring a specific policy or resource for a single workload (use resilience-hub-getting-started), to step-by-step lifecycle execution (see aws-resilience-lifecycle), or to service-specific setup.

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Selects, investigates, and compares AWS object, file, and block storage services, and answers cost, performance, configuration, security, and troubleshooting questions about storage services. Applies when a user asks where to store or archive data based on their usage patterns; which storage service to choose or how two compare; how to migrate data from on-premises or between AWS services; how to protect, replicate, or recover data; how to optimize storage costs; where to deploy shared NFS, SMB, or POSIX file systems; where to store vector embeddings or tabular data; what storage backs enterprise file shares, self-managed databases on EC2, VMware, or stateful containers; or asks what an AWS storage service can do or how it works. Relevant for storage needs for workloads such as AI/ML, analytics, EDA, HPC, media, genomics, or financial trading. Not applicable for SQL query engines (Athena, Spark, Redshift, EMR), ETL (Glue), streaming (Kafka, MSK, Kinesis), or managed database services (RDS, Aurora, DynamoDB).

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Deploys, queries, and debugs AWS Marketplace usage-based (PAYG) metering — the pipeline (ResolveCustomer, BatchMeterUsage, EventBridge via SAM) and querying/debugging metering records, statuses, failures, discrepancies. Covers Concurrent Agreements (CustomerAWSAccountId + LicenseArn), multi-product, CloudTrail Event History (90 days; never CloudTrail Lake), Seller Reports (Billed Revenue/Usage columns + CSV/SDDS parsing), existing-stack detection, metering region for BatchMeterUsage/MeterUsage (DisabledApiException), metered AMI/Container + IAM roles, where registration data lives (customer-profile table), legacy ProductCode + CustomerIdentifier, DuplicateRecord/CustomerNotSubscribed, bad LicenseArn. Also SCOPES adjacent asks — flat-rate/SaaS-Subscription "do I still meter", CCP included-units + overage, contract term/annual renewal, forecasting future bills/usage — with the right answer or a one-line redirect. Use for any BatchMeterUsage/ResolveCustomer or SaaS usage-billing question.

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Assemble a minimal redacted Attio diagnostic bundle with request fingerprints, schema context, retry evidence, and environment metadata. Use when escalating an Attio integration failure without leaking CRM data or secrets. Trigger with "Attio debug bundle", "Attio support evidence", or "collect Attio diagnostics".

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Produce a redacted AssemblyAI diagnostic bundle for support and incident triage. Use when evidence is needed without exposing keys, URLs, audio, transcripts, or prompts. Trigger with "AssemblyAI debug bundle" or "support evidence".

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Harden an Attio integration with least-privilege credentials, tenant isolation, log redaction, raw-body webhook verification, idempotency, and incident-ready rotation. Use when reviewing Attio security controls or preparing production access. Trigger with "Attio security", "secure Attio integration", or "Attio webhook signature".

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Classify Adobe failures from redacted response evidence and select the smallest bounded recovery. Use across auth, Firefly, Photoshop, PDF Services, Events, and App Builder. Use when the task requires adobe response-led error triage. Trigger with "fix Adobe error", "Adobe 403", or "Adobe API failed".

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Produce a PHI-minimized Abridge support bundle with provenance, redaction, and protected escalation boundaries. Use when support needs reproducible evidence for an Abridge issue. Trigger with "build an Abridge debug bundle".

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Instrument Adobe integrations with redacted structured logs, request/job/activation correlation, service-level indicators, alerts, and evidence retention. Use when the task requires adobe content-safe observability. Trigger with "monitor Adobe API", "Adobe observability", or "App Builder logs".

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。