「sentinel」の検索結果

Use this skill when the user is invoking doca_flow_dpa_perf on DPA-capable hardware (ConnectX-7 minimum supported, ConnectX-8 recommended, or BlueField-3) to measure rule update / disable rates on the DPA-offloaded DOCA Flow path — picking the active / passive device split, choosing workload-shape axes (burst, queue, completion threshold, workers, hash pipe algo, PSL tables), or reading Kops/sec iteration stats and the optional self-test. Trigger even when the user does not explicitly mention "doca_flow_dpa_perf" or "DPA Provider" — typical implicit phrasings include "how fast can the DPA program path-selector entries", "baseline rule-update rate on ConnectX-8", "tool reports zero ops on my BlueField", "self-test sentinel never shows on tcpdump", or "is my BlueField-2 DPA-capable". Refuse and route elsewhere for the host / DPU-CPU Flow path (doca-flow-perf), Flow pipeline tuning (doca-flow-tune), writing doca-flow / doca-dpa applications, or DOCA install — those belong to other skills.

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。

Idiomatic Golang error handling — creation, wrapping with %w, errors.Is/As, errors.Join, custom error types, sentinel errors, panic/recover, the single handling rule, structured logging with slog, HTTP request logging middleware, and samber/oops for production errors. Built to make logs usable at scale with log aggregation 3rd-party tools. Apply when creating, wrapping, inspecting, or logging errors in Go code. For samber/oops specifics → See `samber/cc-skills-golang@golang-samber-oops` skill; for slog handler ecosystem → See `samber/cc-skills-golang@golang-samber-slog` skill.

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。

Configure Redis for caching and data storage. Set up clustering, persistence, and Sentinel. Use when implementing Redis caching or queues.

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 policy as code with OPA, Sentinel, and Kyverno. Automate policy enforcement in CI/CD and infrastructure. Use when enforcing compliance through automation.

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。

Work with hyperspectral and multispectral images in MATLAB. Covers reading/writing (ENVI, NITF, TIFF, Sentinel-2, Landsat, ASTER), ECOSTRESS spectral libraries, processing (calibration, atmospheric correction, denoising, sharpening, dimensionality reduction, endmember extraction, unmixing, target/anomaly detection, spectral indices, segmentation), labeling (Spectral Image Labeler app, ground truth objects, automation algorithms), and deep learning (pixel classification CNNs, unmixing autoencoders, transfer learning). Use when reading, writing, processing, analyzing, classifying, labeling, or applying deep learning to hyperspectral or multispectral images.

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。

Pre-flight privilege and work-product check for legal AI prompts. Use when the user is about to send legal content to a third-party AI surface (ChatGPT, Claude.ai, Copilot, Gemini, etc.) and wants to know whether the prompt risks blowing attorney-client privilege or work-product protection. Returns a SAFE/CAUTION/STOP band with cited factors, a discovery-impact line, and a redacted-safe rewrite.

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。

Orientação LGPD para operações de tratamento no Brasil. Cobre bases legais (Art. 7º e Art. 11), RIPD, incidentes (Arts. 48-49), direitos dos titulares (Art. 18) e transferências internacionais. Triggers: LGPD, RIPD, ANPD, proteção de dados, dados pessoais, consentimento, encarregado, DPO Brasil, incidente de dados, legítimo interesse.

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。

GDPR Data Protection Impact Assessment (DPIA) guidance under Article 35 GDPR, EDPB Guidelines WP 248 rev.01, EDPB Opinion 28/2024 (AI), and national SA blacklists/whitelists. Triggers: "DPIA", "DSFA", "Datenschutz-Folgenabschätzung", "impact assessment", "Art. 35", "do I need a DPIA", descriptions of new high-risk processing (profiling, AI, biometrics, large-scale monitoring, special category data), Art. 36 prior consultation questions, national blacklist/whitelist queries.

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。

Elite incident response and legal compliance guidance for data breaches under GDPR Articles 33 & 34. Use when: (1) User reports a data breach or security incident — including "is this even a personal data breach?" triage, (2) User asks about breach notification obligations or deadlines, (3) User mentions "72 hours", Art. 33, Art. 34, or notification requirements, (4) Discussion involves security incidents affecting personal data, (5) User needs breach risk assessment using ENISA methodology, (6) User mentions "Data Breach" or "Incident" or "Data Leakage" or "Ransomware" or "Exfiltration", (7) User needs to determine Controller vs Processor obligations, (8) Cross-border breach scenarios requiring Lead SA determination, (9) User needs a mitigation playbook or immediate response recommendations, (10) User needs audit-ready breach documentation (.docx) or an EDPB-template-aligned breach notification / evidence file — including follow-up and withdrawal notifications, (11) Breach involves an AI system requiring AI Act Art. 73 serious incident screening.

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。

Orientação completa sobre conformidade com regulamentações do Banco Central do Brasil: Resolução CMN nº 4.893/2021 (Política de Segurança Cibernética), Resolução BCB nº 85/2021 (GRSIC), Open Finance Brasil (Resoluções BCB nº 32/2020 e atualizações), e demais normas prudenciais do BACEN. Cobre elaboração e revisão de Política de Segurança Cibernética, Plano de Ação e Resposta a Incidentes (PARI), Gestão de Riscos de Serviços de Informação e Comunicação (GRSIC), consentimento e compartilhamento de dados no Open Finance, requisitos de API, gestão de terceiros (outsourcing) e sanções do BACEN. Triggers: Bacen, Banco Central, CMN 4.893, Resolução 4.893, segurança cibernética bancária, PARI, GRSIC, Open Finance, Open Banking, compartilhamento de dados financeiros, consentimento Open Finance, API financeira, outsourcing bancário, risco cibernético, incidente cibernético banco, LGPD financeira, fintech compliance, instituição financeira, DICT, Pix segurança.

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。

Expert knowledge for Azure Web Application Firewall development including best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring Front Door/App Gateway WAF rules, geo/bot filters, rate limits, Sentinel logging, or APIM/Azure OpenAI protection, and other Azure Web Application Firewall related development tasks. Not for Azure Application Gateway (use azure-application-gateway), Azure Front Door (use azure-front-door), Azure Firewall (use azure-firewall), Azure Firewall Manager (use azure-firewall-manager).

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。

Expert knowledge for Azure Oracle development including troubleshooting, security, and integrations & coding patterns. Use when configuring Oracle TDE with Azure Key Vault, fixing Oracle@Azure issues, or exporting Exadata logs to Azure Monitor/Sentinel, and other Azure Oracle related development tasks. Not for Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines), SAP HANA on Azure Large Instances (use azure-sap).

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。

Expert knowledge for Azure Lighthouse development including decision making, security, configuration, integrations & coding patterns, and deployment. Use when configuring Lighthouse delegations, AOBO/PIM access, Arc/Sentinel integrations, policies/remediation, or Marketplace offers, and other Azure Lighthouse related development tasks. Not for Azure Arc (use azure-arc), Azure Managed Applications (use azure-managed-applications), Azure Resource Manager (use azure-resource-manager), Azure Role-based access control (use azure-rbac).

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 the user asks to refresh CLAUDE.local.md, regenerate project context, or after a brain-update session flush. Rewrites only the sentinel-delimited auto-generated section from the brain DB, preserving manual behavior rules.

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。

Standards for error wrapping, checking, and definition in Golang. Use when wrapping errors, defining sentinel errors, or handling errors idiomatically in Go.

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。

Scope or freeze which files Claude can edit during debugging, a refactor, or review. Use when edits should stay in specific dirs, or for a read-only investigate lock. Backed by a sentinel + PreToolUse hook.

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。

Engineer and audit SIEM detection rules — log source coverage, Sigma / KQL / SPL / Elastic query authoring, MITRE ATT&CK mapping, false-positive tuning, and detection-as-code workflows. Use when the user mentions 'SIEM,' 'detection engineering,' 'detection rules,' 'Sigma,' 'KQL,' 'SPL,' 'Splunk,' 'Sentinel,' 'Elastic,' 'Wazuh,' 'Chronicle,' 'detection-as-code,' 'MITRE ATT&CK mapping,' 'log coverage,' 'alert tuning,' 'use case development,' or needs help building or improving security detections.

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。

Puts oaustegard/muninn-utilities on the container Python path — runs scripts/boot.sh, which shallow-clones the repo (codeload tarball as fallback) and writes the .pth. The boot payload itself comes from the Muninn MCP connector: call its `boot` tool after this script. Trigger on the first message of any new Muninn conversation, or when the user says "boot up" / "boot" — unless the message contains "skip boot". Idempotent: a warm container exits in ~0s via a sentinel.

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。

Analyzing code statically for security flaws: hardcoded secrets, SQL injection, input validation, security headers, dependency CVEs. Not for runtime exploit checks (Probe) or code review (Judge).

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。

Scanning and eradicating supply-chain malware (Shai-Hulud/S1ngularity npm/PyPI worms): IoC scan, OS/IDE persistence, safe credential rotation. Not for SAST (Sentinel) or skill/MCP audit (Chain).

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。

Integrating OWASP ZAP/Burp Suite/Nuclei, planning penetration tests, executing DAST, and scanning for vulnerabilities. For runtime vulnerability validation. Complements Sentinel static analysis.

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。

Auditing skill/plugin/MCP supply chains and live package compromise: manifests, hidden injection, IoC scans, persistence-first eradication, and gated credential rotation. Not for app SAST (Sentinel).

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 at write time to vector/embedding memory — Grove content-addressed insertion, chroma/pgvector upserts, memory-consolidation promoting session traces to MEMORY.md, or embedding externally-ingested content. Scores each candidate record against a fixed panel of sentinel queries and quarantines any record that would become the nearest neighbor of too many unrelated queries — a hub — whether from adversarial poisoning or accidental over-generality. This is the memory-record-side sibling of skill-injection-guardian (file-side) and the write-side complement of memory-use-warrant (read-side). Quarantine, never silently drop; a human reviews. Backed by the admission-time hubness gate (arxiv 2606.19692v1). Triggers on inserting into vector memory, consolidating memory, and embedding stranger content.

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。

Launches and supervises long-running commands — solves, workflows, downloads, builds — detached with a log, PID and exit sentinel, then tells stuck from slow and kills verifiably. Use before running anything that may exceed a minute, for nohup or background launches, and when a run hangs, shows no output, or timed out.

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。