「address」の検索結果

This skill covers detecting anomalies in Modbus/TCP and Modbus RTU communications in industrial control systems. It addresses function code monitoring, register range validation, timing analysis, unauthorized client detection, and deep packet inspection for malformed Modbus frames. The skill leverages Zeek with Modbus protocol analyzers, Suricata IDS with OT rules, and custom Python-based detection using Markov chain models for normal Modbus transaction sequences.

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。

This skill covers deploying anomaly detection systems for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications. It addresses building normal behavior profiles for SCADA polling patterns, detecting deviations in Modbus/DNP3/OPC UA traffic, identifying rogue devices, and correlating network anomalies with physical process data from historians.

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。

Detect abnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics. Identifies after-hours bulk downloads, access from new IP addresses, unusual API calls (GetObject spikes), and potential data exfiltration using statistical baselines and time-series anomaly detection.

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。

Analyzes indicators of compromise (IOCs) including IP addresses, domains, file hashes, URLs, and email artifacts to determine maliciousness confidence, campaign attribution, and blocking priority. Use when triaging IOCs from phishing emails, security alerts, or external threat feeds; enriching raw IOCs with multi-source intelligence; or making block/monitor/whitelist decisions. Activates for requests involving VirusTotal, AbuseIPDB, MalwareBazaar, MISP, or IOC enrichment pipelines.

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。

Detect and analyze heap spray attacks in memory dumps using Volatility3 plugins to identify NOP sled patterns, shellcode landing zones, and suspicious large allocations in process virtual address space.

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。

Monitor PRs, fix CI failures, address review comments, resolve merge conflicts, and restack stacks. Supports independent PRs, Graphite stacks, and GitHub stacked PRs (gh-stack).

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。

Iterate on a PR until actionable CI passes and high/medium review feedback is addressed. Use for PR CI failures, review feedback, or green-check loops; do not wait for human approval, draft status, or merge gates.

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。

Generate a compact PDF shipping label with sender and recipient addresses, barcode, and tracking number.

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。

Generate a packing slip PDF with order details, item list, and shipping address.

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。

Generate a branded property listing graphic with a property photo, status badge, price, address, and key stats.

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。

Extract property address, price, room count, and features from a listing document into structured JSON for MLS and property platforms.

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。

Extract address, listing price, bedrooms, bathrooms, amenities, and agent contact details from a public listing page.

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。

Use when designing inclusive animations, addressing vestibular disorders and motion sensitivity, or ensuring animation accessibility compliance.

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。

デジタル庁 アドレス・ベース・レジストリ(ABR)の公式マスタ(都道府県・市区町村・町字)で日本の住所文字列を分解・正規化する。全国47都道府県・1,918市区町村・町字レコードを使い、住所から都道府県・市区町村(全国地方公共団体コード)・町字(町字ID)・番地を切り出す。表記ゆれ(漢数字/全角/半角の丁目、郡名省略、都道府県名省略)を吸収。APIキー・ログイン不要。住居表示の番地・号の正規化やジオコーディング(緯度経度)は対象外。

Use CodeRabbit CLI to receive external code review feedback and address identified issues. Invoke this skill when the user requests CodeRabbit review, or proactively after implementing significant code changes to get feedback and improve code quality.

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。

Address unresolved review comments on specified PR

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。

Scan Gmail (default: today's inbox), produce an anonymized summary with action points, then export each email to Linear as an issue with a sensible priority. No personal details — names, email addresses, or company identifiers — ever leave the summary or reach Linear. Use when the user types /gmail-linear-exports, or asks to turn their inbox into Linear issues / export emails to Linear.

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。

Delimits putative species boundaries from molecular data within the de Queiroz 2007 unified-lineage framework using ASAP (Puillandre 2021 successor to ABGD), mPTP C++ (Kapli 2017 successor to bPTP; bPTP is Python NOT R), GMYC single/multi-threshold (Pons 2006; Fujisawa 2013), multilocus BPP v4 with prior calibration from data (NOT defaults; Yang 2015), SNAPP + BFD* for SNP delimitation, DELINEATE (Sukumaran 2021) speciation-process modeling to address Sukumaran & Knowles 2017 PNAS critique that MSC delimits structure not species, integrative-taxonomy congruence (Padial 2010; Carstens 2013), Dsuite for introgression testing before sister claims (Malinsky 2021), and Meyer & Paulay 2005 barcoding-gap-absence caveat. Use when delineating species from DNA barcoding data, resolving cryptic complexes, choosing among ASAP/mPTP/BPP/DELINEATE, calibrating BPP priors, distinguishing introgression from ILS, or applying the Sukumaran-Knowles oversplitting correction.

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。

Designs and analyzes in vivo CRISPR screens in animal tumor models, organoids, and immune-cell adoptive transfers. Covers bottleneck math (250x cells/sgRNA requires ~25M cells implanted; impossible for most syngeneic models, forcing focused libraries), focused library design (Manguso 2017 Nature 547:413 immune screen; Chen 2015 tumor screens), CRISPR-StAR intrinsic-control screening (Uijttewaal 2025 Nat Biotechnol 43:1848), clonal-dynamics-limited detection, tumor-explant DNA recovery, syngeneic vs xenograft vs PDX considerations, and the relationship to downstream MAGeCK / drugZ analysis. Use when designing in vivo CRISPR screens for tumor / immune / metastasis biology, choosing focused vs genome-wide for animal models, addressing bottleneck-induced clonal collapse, picking the syngeneic / xenograft / PDX model, integrating in vivo with in vitro results, or applying CRISPR-StAR for animal experiments.

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。

Refactor Spring Boot and Java code to improve maintainability, readability, and adherence to enterprise best practices. This skill transforms messy Spring Boot applications into clean, well-structured solutions following SOLID principles and Spring Boot 3.x conventions. It addresses fat controllers, improper transaction boundaries, field injection anti-patterns, and scattered configuration. Leverages Java 21+ features including record patterns, pattern matching for switch, virtual threads, and sequenced collections.

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。

Azure Maps SDK for .NET. Location-based services including geocoding, routing, rendering, geolocation, and weather. Use for address search, directions, map tiles, IP geolocation, and weather data.

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。

Sweep addressed callouts older than a threshold (default 180 days) into the target note's

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。

Generate a backward-looking retrospective of vault activity (addressed callouts + Log entries) over a time window (1w / 1m / 1q), overlay with newsflow + earnings transcripts + price action, and rank trade ideas by the gap between official narrative and market reaction. Output is an immutable Research note. Use when user says "retro", "retrospective", "what did I do this week/month/quarter", "review activity against market", or "recommend trades from recent research".

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。

Read all suggested PR changes and apply them directly to the codebase. Use when you have PR review comments to address, suggested changes to implement, or feedback to incorporate into your code.

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。