「ods」の検索結果

Use when reviewing sign-in, sign-up, MFA, CAPTCHA, recovery, and re-auth flows. Evaluate the full authentication path, including error handling and backup methods, not just the primary login form.

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Protocol-driven study screening for systematic, scoping and rapid reviews. Turns a proposal or PROSPERO protocol into confirmed eligibility rules, then screens titles/abstracts and full texts with two blinded AI reviewers and a third-reviewer adjudicator: ordered exclusion codes, no silent defaults, resumable batch runs, QC (seed studies, near-miss rechecks, kappa and PABAK), PRISMA 2020 counts, EndNote/Zotero RIS groups, an Excel log, a methods draft and a literature_corpus handoff to academic-paper. Reads RIS, PubMed .nbib, Web of Science and CSV exports; removes duplicates. 8 modes: protocol, quick, pilot, ta-screen, ft-screen, adjudicate, audit, report. Use it to screen records against eligibility criteria, pilot screening, resolve screening conflicts, audit exclusions or report the selection process. Triggers on: screen these papers, title/abstract screening, full-text screening, screening conflicts, inclusion criteria, PRISMA flow, غربالگری مقالات, اسکرینینگ عنوان و چکیده, معیارهای ورود و خروج.

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Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze experimental or survey data, check statistical assumptions, compute required sample sizes, or write up results - even if they never name a specific test. Covers t-tests, ANOVA, chi-square, correlation, regression, non-parametric and Bayesian methods. For low-level model APIs, see the statsmodels and pymc skills.

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Prepares evidence-bounded, constructive peer-review drafts and structured manuscript assessments. Supports authorized review of scientific manuscripts, protocols, preprints, or research proposals; reporting-guideline selection; claim–evidence checks; methods, statistics, reproducibility, ethics, figure/table, and citation critique; or revision-response planning.

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Guides protocol selection, input preparation, pricing checks, and browser ordering on Ginkgo Bioworks Cloud Lab (cloud.ginkgo.bio). Applies to cell-free, E. coli, and Pichia protein expression; HiBiT, A280, and LabChip readouts; IVT mRNA/circRNA synthesis; thermal shift assays; Echo-MS methods; SPR target onboarding; plate-reader assay onboarding; and fluorescent pixel art.

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Build a structured deep-reading Paper Card for one scientific paper, analysing methods, experiment-to-claim evidence, limitations, and research ideas. Use for 论文精读卡、方法拆解、证据链分析; not full-paper bilingual translation or formal peer review.

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Binance P2P trading assistant for natural-language queries about P2P/C2C market ads, the user's own P2P order history, order detail & appeal tracking, and advertisement publish & management. Use when the user asks about P2P prices, searching/choosing ads, comparing payment methods, reviewing P2P order history, checking order detail/appeal status, querying complaints, publishing/updating/managing P2P advertisements, or viewing merchant profiles. Do NOT use for spot/futures prices, exchange trading, deposits/withdrawals, on-chain transfers, or anything unrelated to P2P/C2C.

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Query Binance fiat payment capabilities — supported countries, currencies, payment methods, limits, and crypto prices — via public APIs, plus authenticated order/payment history lookup. Use whenever users ask about buying or selling crypto with fiat, depositing or withdrawing fiat, fiat-crypto exchange rates, payment options in a specific country, or their fiat order history — even if they don't explicitly mention Binance APIs.

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Scaffold a new CCXT exchange integration in TypeScript, following the certified-exchange template. Walks through describe(), required unified methods, parsers, capability flags, sandbox setup, and static fixtures. Use when adding support for an exchange that does not exist yet under ts/src/.

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Binance Onchain Pay enables users to buy cryptocurrency with fiat (e.g., EUR, USD) or send existing crypto from their Binance account directly to any external on-chain wallet address in a single flow—no manual withdrawal needed. Enables partners to integrate crypto buying services: - payment-method-list: Get available payment methods (Card, P2P, Google Pay, Apple Pay, etc.) with limits for a fiat/crypto pair - trading-pairs: List all supported fiat currencies and cryptocurrencies - estimated-quote: Get real-time price quote including exchange rate, fees, and estimated crypto amount - pre-order: Create a buy order and get redirect URL to Binance payment flow - order: Query order status and details (processing, completed, failed, etc.) - crypto-network: Get supported blockchain networks with withdraw fees and limits - p2p/trading-pairs: List P2P-specific trading pairs

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Binance Pay Assistant - Send and Receive crypto payments. Send: QR code payment from Funding Wallet (C2C + PIX). Use when user wants to buy/purchase/pay/transfer/send, confirm/cancel payment, or query order status. Requires QR code data. PIX QR codes (pix, br.gov.bcb.pix) are auto-detected. Receive: Generate QR codes and payment links to collect crypto. Use when user wants to receive/collect payment (generate receive link, receive QR). Do NOT use for earning, buying/selling crypto, or digital goods.

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Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for Kubernetes API analysis, service-account trust, RBAC edges, admission and controller behavior, cluster secrets, workload mutation, and namespace-scoped drift. Use when the user asks to inspect kube API permissions, service-account tokens, RoleBinding or ClusterRoleBinding edges, admission webhooks, controller-created pods, secret exposure, or why live workloads differ from manifests. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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Decide whether to fine-tune at all, and route to the right method (SFT, DPO/ORPO/KTO, GRPO/RLVR, continued pretraining) and base model. Use when starting any fine-tuning effort, when unsure whether RAG or prompting would suffice, or when choosing between preference-optimization and reinforcement methods.

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Align a fine-tuned model with preference data using DPO, ORPO, KTO, or SimPO. Use when preference pairs or thumbs-up/down feedback exist, when choosing between preference-optimization methods, or when a DPO run needs hyperparameters or debugging.

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Implement Kubernetes security policies including NetworkPolicy, PodSecurityPolicy, and RBAC for production-grade security. Use when securing Kubernetes clusters, implementing network isolation, or enforcing pod security standards.

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Look up Microsoft API references, find working code samples, and verify SDK code is correct. Use when working with Azure SDKs, .NET libraries, or Microsoft APIs—to find the right method, check parameters, get working examples, or troubleshoot errors. Catches hallucinated methods, wrong signatures, and deprecated patterns by querying official docs.

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Creates an integration testing plan for .NET data access artifacts during Oracle-to-PostgreSQL database migrations. Analyzes a single project to identify repositories, DAOs, and service layers that interact with the database, then produces a structured testing plan. Use when planning integration test coverage for a migrated project, identifying which data access methods need tests, or preparing for Oracle-to-PostgreSQL migration validation.

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Refactoring using Extract Methods in Java Language

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Technology-agnostic prompt generator that creates customizable AI prompts for scanning codebases and identifying high-quality code exemplars. Supports multiple programming languages (.NET, Java, JavaScript, TypeScript, React, Angular, Python) with configurable analysis depth, categorization methods, and documentation formats to establish coding standards and maintain consistency across development teams.

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Analyze unit economics for PE targets — ARR cohorts, LTV/CAC, net retention, payback periods, revenue quality, and margin waterfall. Essential for software/SaaS, recurring revenue, and subscription businesses. Use when evaluating revenue quality, building a cohort analysis, or assessing customer economics. Triggers on "unit economics", "cohort analysis", "ARR analysis", "LTV CAC", "net retention", "revenue quality", or "customer economics".

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Quantitative statistical methods: ADF unit-root / cointegration tests, GARCH volatility modeling, regression diagnostics (heteroskedasticity / autocorrelation), Bootstrap, and hypothesis testing.

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Exploits privileged pods, host mounts, runC CVEs, and exposed Docker sockets to break out of a container and reach the underlying host during an authorized container-security assessment. Use when executing an approved breakout test, demonstrating the real impact of a privileged or hostPath workload, or validating that escape mitigations actually hold. Keywords: container breakout, privileged, hostPath, docker.sock, runC CVE-2019-5736, CVE-2024-21626, release_agent, nsenter. Do not use for defensive detection of these techniques - use detecting-container-escape-attempts.

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Detect Layer 2 ARP poisoning/spoofing by deploying ARPWatch, Dynamic ARP Inspection (DAI), Wireshark packet analysis, and custom Python monitoring scripts that flag gratuitous ARP floods, IP-to-MAC mapping changes, and duplicate IP addresses. Use when investigating suspected man-in-the-middle interception or session hijacking on a local network segment, or when building layer-2 anomaly detection for a SOC.

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Detect data exfiltration via DNS tunneling (tools like iodine, dnscat2, dns2tcp) by analyzing query entropy, subdomain length, query volume to single domains, TXT/CNAME/NULL record abuse, and oversized response payloads using passive DNS monitoring and statistical/ML methods. Use when hunting for covert DNS-based data exfiltration or building a passive DNS anomaly detection capability.

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。