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Set up and troubleshoot the WizTelemetry Notification extension for KubeSphere. Configure delivery channels such as email and Slack, route alerts by labels, silence notifications for scheduled periods, and search notification history to investigate delivery problems.
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Investigate an alert or suspicious identifier using logs and source code. Assess attack success, measure affected data and users, test the suspected flaw locally, and produce a response plan for human review and execution.
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Turns one-shot external recon into a continuous monitoring program. Covers the scheduled re-scan-and-diff loop (baseline snapshot -> interval sleep -> re-scan -> asset/finding delta -> threshold-gated webhook alert), the scan-to-scan diff engine (new/removed/changed assets by a tracked-attribute table, new/resolved findings by a stable cross-scan fingerprint), adversary CTI / chatter monitoring across six public feeds (ransomwatch, ransomware.live, HackerNews Algolia search, Reddit security-subreddit RSS, GitHub Gist code-search, public Telegram channel scraping) with a source-kind-aware severity engine (leak-site/forum/telegram/paste tiers, CRITICAL through INFO), literal/glob/regex watchlist pattern matching, full-corpus capture with retroactive rescan on new watchlist entries, infrastructure-tracking-over-time discipline (certificate-transparency, passive-DNS, port/service, and typosquat re-enumeration cadence, and what a genuine 'perimeter drift' event looks like in the diff output), a five-state finding-lifecycle state machine (open/triaged/risk_accepted/resolved/false_positive) with per-severity SLA and fingerprint-based cross-scan dedup and auto-resolve/reopen rules, the alert-fatigue trap where a lifecycle-unaware rule re-fires on an already-accepted finding, a durable retry/backoff alert-outbox pattern ('queued is not delivered'), and copy-paste bash-cron plus PowerShell-Scheduled-Task recipes for a re-scan+diff loop with the Slack-compatible webhook payload shape. Passive OSINT and analysis only -- no new active-intrusion technique. Use when setting up ongoing monitoring for a retainer or MSSP engagement, tuning alert thresholds to avoid fatigue, triaging a finding's lifecycle status, investigating adversary chatter about a brand, building a 'what changed on the perimeter since last week' report, or deciding whether a persisting finding should re-alert.
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Inspect fired CCAM alerts and manage alert rules for token thresholds, event patterns, inactivity, and status duration. Use when acknowledging alerts, creating or editing a rule, checking cooldowns, or connecting alert rules to webhook targets.
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Design and run a monitoring system for a website or web app. Use this skill when setting up uptime checks, defining SLOs, configuring error tracking, choosing what to alert on, designing on-call rotations, or fixing alert fatigue. Triggers on monitoring, alerts, uptime, SLO, SLA, error rate, on-call, pager, alert fatigue, observability, dashboards, what should we monitor. Also triggers when an incident reveals a gap in monitoring.
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Build, run, and improve a Security Operations Center — alert prioritization, runbook authoring, escalation criteria, on-call structure, alert tuning workflow, MTTD / MTTR / fidelity KPIs, analyst tiering, and shift handoffs. Use when the user mentions 'SOC,' 'security operations,' 'SOC analyst,' 'alert triage workflow,' 'runbook,' 'escalation,' 'on-call,' 'SOC tiering,' 'tier 1 / tier 2,' 'MTTD,' 'MTTR,' 'alert fatigue,' 'alert tuning,' 'shift handoff,' 'SOAR,' or wants to design or improve a security operations team.
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Use when the repository keeps its alerting in code, or a person asks for alerts outside TaskTrooper - PrometheusRule YAML, a Cloud Monitoring alert policy in Terraform, a Datadog monitor, each routed to TaskTrooper's alert ingest URL so it opens an incident here
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Analyze production Agentforce agent behavior using session traces and Data Cloud, and manage Agent Health Monitoring (AHM) alerts. TRIGGER when: user queries STDM session data or Data Cloud trace records; investigates production agent failures, regressions, or performance issues; asks about session traces, conversation logs, or agent metrics; wants to reproduce a reported production issue in preview; runs findSessions or trace analysis queries; creates, lists, updates, or deletes an AHM data alert on an agent metric (escalation rate, deflection, etc.); asks why an alert is not firing or wants to check whether alerts have fired (notification counts, or the per-alert Incidents view). DO NOT TRIGGER when: user creates, modifies, or debugs .agent files during development (use agentforce-generate); writes or runs test specs (use agentforce-test); uses sf agent preview for local development iteration; deploys or publishes agents.
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Medicinal chemistry filters for compound triage. Apply drug-likeness rules (Lipinski rule of five, Veber, Oprea, CNS, lead-like, rule of three), structural alert catalogs (PAINS a/b/c, NIBR screening-deck severity, Brenk, BMS, Glaxo, Dundee, ChEMBL common alerts), ZINC-15 percentile complexity metrics (Bertz, SAscore, QED, Whitlock, Barone), chemical-group detection, Lilly demerits, and the medchem query language (MATCHRULE, HASALERT, HASPROP, HASGROUP) for filtering a library at scale. Also trigger on medchem, `import medchem as mc`, RuleFilters, NIBRFilters, CommonAlertsFilters, NamedCatalogs, QueryFilter, PAINS filtering, or structural alerts.
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Use this skill when an auditor, customer or regulator will ask how security events are logged and watched, and someone says "prepare logging evidence", "show we monitor alerts", "what do we log and for how long", "who looks at the SIEM", "prove an alert was handled" or "our monitoring evidence is just dashboard screenshots". Maps log coverage and retention per system, lists the alert rules that matter and where they go, traces real alerts end to end with timestamps, and writes an evidence pack with the gaps stated plainly.
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处理OpenClaw的GitHub Secret Scanning警报，检查凭据泄露位置，遮盖正文中的机密信息，删除并重建评论，通知作者并完成警报处理。
将视频和音频导入VideoDB，按语音或画面搜索场景并制作片段，还可添加字幕和音轨、调整画面比例、设置直播事件通知，以及记录和总结桌面操作。
用于开发嵌入电子病历的临床决策支持，涵盖药物相互作用、剂量验证和临床评分，并按警报严重程度设计界面行为及检测漏报警的测试。
Create and tune Falco rules to detect possible container escapes, where a container gains access to its host. Define detection conditions, alert priorities, and output fields, then refine exceptions to reduce false positives.
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Deploy decoy credentials, documents, and URLs with Canarytokens to detect suspicious access. Guides token generation, placement, alert testing, and inventory tracking, with email or webhook notifications when someone interacts with a planted token.
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Set up decoy files on endpoints and shared folders to detect possible ransomware activity. Monitor modifications, deletions, and renaming with file monitoring tools, connect events to alerts, and test whether the detection and response process works.
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Set up decoy credentials, storage, and secrets across AWS, Azure, and GCP to detect suspicious access. Connect audit logs to security alerts, verify detection, and document permissions, resource inventories, and maintenance plans.
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Create automated workflows that add threat intelligence to suspicious IP addresses, domains, URLs, and file hashes. Combine findings from multiple services into consistent alert context and confidence scores to support analysts reviewing security alerts.
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Design a product metrics dashboard with clearly defined measures, data sources, charts, targets, and alert thresholds. The skill produces a Markdown specification that also covers dashboard layout, review schedules, and responsibilities for responding to alerts.
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Configure GKE logging, metrics collection, dashboards, and alerts with Cloud Logging, Cloud Monitoring, and managed Prometheus. Diagnose missing measurements, collection failures, permission errors, and alert rule problems to identify appropriate configuration changes.
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Monitor daily AWS spending by service and account, compare it with historical baselines, and send Slack alerts with cost differences and likely causes. Known planned increases are excluded, and cloud resources remain unchanged.
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Track machine learning experiments with Trackio by recording training measurements, viewing live dashboards, and flagging diagnostic events. Retrieve metrics and alerts through command-line queries, with JSON output for automated monitoring and experiment review.
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Hunt for signs of compromise in web and application logs without an initial alert. Establish normal activity, record investigative hypotheses, check source code, and reproduce issues locally before producing incident records and a report.
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Set up alerting rules, configure on-call rotations, and manage incident response workflows. Integrate with PagerDuty, Opsgenie, or Grafana OnCall for alert routing and escalation. Use when implementing alerting strategies and on-call management for production systems.
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