「db」の検索結果

Detects and prevents code injection attacks targeting serverless functions (AWS Lambda, Azure Functions, Google Cloud Functions) through event source poisoning, malicious layer injection, runtime command execution, and IAM privilege escalation via function modification. The analyst combines static analysis of function code, CloudTrail event correlation, runtime behavior monitoring, and IAM policy auditing to identify injection vectors across the expanded serverless attack surface including API Gateway, S3, SQS, DynamoDB Streams, and CloudWatch event triggers. Activates for requests involving Lambda security assessment, serverless injection detection, function event poisoning analysis, or serverless privilege escalation investigation.

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。

Responds to phishing incidents by analyzing reported emails, extracting indicators, assessing credential compromise, quarantining malicious messages across the organization, and remediating affected accounts. Covers email header analysis, URL/attachment sandboxing, and mailbox-wide purge operations. Activates for requests involving phishing response, email incident, credential phishing, spear phishing investigation, or phishing remediation.

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。

Implement a phishing report button in email clients with automated triage workflow that analyzes user-reported suspicious emails and provides feedback to reporters.

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 network traffic generated by malware during sandbox execution or live incident response to identify C2 protocols, data exfiltration channels, payload downloads, and lateral movement patterns using Wireshark, Zeek, and Suricata. Activates for requests involving malware network analysis, C2 traffic decoding, malware PCAP analysis, or network-based malware 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。

Full dev cycle. Planning tier for clarify and plan; worker tier after approval for autonomous execution, tiered lint, thread rotation, and feedback fixes. Start every change here.

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。

Coach German writing and conversation with minimal corrections, persistent root-cause mistake tracking (FehlerDNA), mistake-based spaced repetition with a new sentence every time, roleplay whose words return in spaced reviews, continuing preparation for real-life goals across sessions, and an honest progress profile. Use for German correction, personalized review, vocabulary, progress, roleplay, or preparation for an interview, presentation, appointment, or other concrete event; do not use for translation-only requests without learning or feedback.

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。

Synthesize user interviews, observations, surveys, support tickets, reviews, or feedback into traceable themes, insights, tensions, opportunities, and research gaps; use when evidence must inform product or design decisions.

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 this skill when you need to review presentation materials from an audience perspective to improve their quality and effectiveness. Evaluates content clarity, visual design, logical flow, engagement factors, and Marp technical compatibility. Triggers include "review my presentation", "check my slides", "presentation feedback", or when a user has completed a draft presentation and wants comprehensive quality review.

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, reviewing, modifying, migrating, optimizing, securing, operating, troubleshooting, or decommissioning data architectures across data model exploration, SQL, ISO SQL conformance, NoSQL, vector, graph, document, time-series, NewSQL, search, in-memory, SQLite, CDC/Debezium, DBMS storage/query/recovery internals, database incident prevention, hardware acceleration, cache, big-data, lakehouse, and warehouse systems.

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。

XP-style plan review that identifies gaps, hidden assumptions, and critical misses. Triggers on 'review the plan', 'check the plan', 'audit the plan'. Reviews plans for YAGNI violations, missing feedback loops, and over-engineering.

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。

Brutally honest AGENTS.md/CLAUDE.md review backed by real A/B test evidence. Not just opinions — actual proof that your rules are dead weight. Roasts instruction files for bloat, slop, and redundancy, then proves it by running evals. Use when user says "roast my agents.md", "roast my CLAUDE.md", "prove my rules are useless", "eval roast", or wants entertaining evidence-based feedback on their AI config files. Also triggers on "audit my instructions" or "are my rules helping".

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。

Turn 'should never happen' into 'cannot happen' by defining owned inductive invariants and enforcing them at parse/construct/API/DB/lock/txn boundaries with a verification signal. Use when prompts mention invariants, impossible states, validation sprawl, cache/index drift, idempotency/versioning, retries/duplicates/out-of-order events, race/linearization bugs, loop correctness, or hardening another workflow (for example /tw-fix) with invariant checks first.

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。

Load for Blazor/MudBlazor UI changes involving forms, dialogs, focus, keyboard navigation, landmarks, ARIA, color contrast, RTL-safe styling, or WCAG 2.2 AA tests; not for backend-only changes.

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。

Load for global UI-system changes involving CSS `@layer`, primitive/semantic/component tokens, themes, reusable MudBlazor wrappers, or design-token governance; not for one component's isolated CSS.

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。

Load for EF Core entities/configurations, semantic value persistence, portable constraints, DbContext/query filters, repositories/specifications, migrations, model snapshots, transactions, or seeded lookup tables; use query-optimization specifically for N+1 or slow SQL diagnosis.

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。

Load for Blazor/MudBlazor component or page changes involving render modes, dialogs, parameters/events, HAL-gated actions, generated API clients or generated record consumption, theming, or component tests; add accessibility or CSS-isolation only when touched.

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。

Load when editing Blazor `.razor.css`, scoped selectors, `::deep`, BEM class names, RTL/logical CSS properties, or styling nested MudBlazor components; not for global design tokens or non-Blazor CSS.

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。

Load for Senior CTO critique, architectural audit, risk review, sequencing correction, or refinement of an existing implementation-plan triad; edits the requested plan/context/tasks in place without creating a worktree or review file. Not for open-ended CTO advice, product implementation, or implementation workspace setup.

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。

Author a completed-spec fixture — a seeded intent graph plus a believable four-phase interview transcript — for a brunch feature, so it can feed any downstream tooling that consumes a completed spec or dogfood the UI. Use when you need a real completed specification in .brunch/brunch.db for testing or demo: pick a feature from memory/SPEC.md (or a free description), choose a stress profile (coverage|clean), and produce a registered scenario seed + an interview-questions doc that match exactly.

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。

豆包 / 微信输入法个人词库：识别、导出、导入、备份；纠错优化； 搜索并生成行业/专业/定制词库（并入归档 industry-dict）。 不走官方导入页。搜索优先 argo，没有就走通用搜索兜底。本技能只出查询、抽词、改表、写回副本。 生态定位：直接操作豆包 / 微信输入法词库文件层（usr.dat / WeType LevelDB）的 agent skill， 文件层识别、批量导出、槽位感知注入、整表替换消错、行业词库造词后直接 apply； 格式互转工具和语音输入插件都不做词库管理。 触发：个人词库、词库导出、词库导入、反向注入、行业词库、专业词库、定制词库、 生成行业词库、做词库、行业术语、industry-dict、拼写纠正、豆包词库、 微信输入法词库、WeType、usr.dat、ime-lexicon、/ime-lexicon

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。

Knowledge base from NASA-STD-8719.14C (Process for Limiting Orbital Debris). Use for orbital-debris assessment planning, mission-related debris limits, explosion/passivation and collision risk, postmission disposal options, reentry casualty risk, and ODAR/EOMP governance. Covers STD-8719.14C (Approved 2021-11-05) synthesized notes only; does not replace NPR 8715.6 delivery timing, NASA-HDBK-8719.14 environment/modeling depth, or program-specific OSMA waivers.

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。

Knowledge base from NASA System Safety Handbook Volume 2 (NASA/SP-2014-612). Use for risk-informed safety cases (RISC), integrated safety analysis (ISA), adequate safety concepts, safety objectives and requirements, acquirer/provider roles, graded safety analysis, claims-evidence-argument structure, SSMP development, and RISC evaluation. Does not cover nuclear or chemical safety domains, occupational health regulations, or NASA-specific programmatic requirements beyond system safety.

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。

Signpost (not a knowledge pack) for the systems-engineering standards landscape — ISO/IEC/IEEE 15288, 24748, 29148, 42010, 15026, 24765; INCOSE SE Handbook & Vision 2035; OMG SysML; SAE/EIA 1001/649/748; ECSS space standards; NATO AAP-48; CMMI; NIST SP 800-160; and more. Contains NO source content: it lists each standard's designation, title, purpose, owning SDO, whether it's redistributable, and where to get it. Use when you need to identify or locate an SE standard — most are paywalled/all-rights-reserved and cannot be packaged, so this points you to the owner (and to the open packs where one exists).

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。