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Found 1,444 Skills
Collect and analyze on-device performance metrics and crash diagnostics using MetricKit. Use when setting up MXMetricManager, handling MXMetricPayload or MXDiagnosticPayload, processing crash/hang/disk-write diagnostics via MXCallStackTree, adding custom signpost metrics, or uploading telemetry to an analytics backend.
Check AI CLI usage/quota for Claude Code, OpenAI Codex, Google Gemini CLI, and Z.AI. Use when user asks about remaining quota, usage limits, rate limits, or wants to check how much capacity is left.
Alibaba Cloud Security Center incident management skill. Query security incidents, threat trends, and incident details. Triggers: "云安全中心", "安全事件", "事件查询", "安全态势", "威胁事件", "cloud-siem", "Agentic-soc".
Lumigo integration. Manage data, records, and automate workflows. Use when the user wants to interact with Lumigo data.
Better Stack integration. Manage Incidents, Users, Teams. Use when the user wants to interact with Better Stack data.
Inspector integration. Manage data, records, and automate workflows. Use when the user wants to interact with Inspector data.
Librato integration. Manage data, records, and automate workflows. Use when the user wants to interact with Librato data.
Manage Jetty workflows and assets. Use when the user wants to create, edit, run, deploy, debug, or monitor AI/ML workflows on Jetty. Also use when they mention collections, tasks, trajectories, datasets, models, labels, step templates, or workflow runs. Triggers include 'run workflow', 'create task', 'list collections', 'check trajectory', 'label trajectory', 'add label', 'deploy workflow', 'show results', 'download output', 'debug run', 'workflow failed', or any Jetty/mise/dock operations. Even if the user doesn't say 'Jetty' explicitly, use this skill whenever they're working with Jetty API endpoints, workflow JSON, or init_params.
Monitors TrueFoundry deployment rollouts after deploy/apply. Polls status, checks pod health and readiness, fetches logs on failure, and reports a final summary. Use after deploying or applying a manifest to track rollout progress.
Track and normalize change requests against the official Megatron-LM repository by branch, PR, commit, commit range, or time window. Use when Codex needs to collect the exact upstream change set before deeper analysis, especially for branch-aware Megatron and MindSpeed migration work, daily/periodic tracking, or preparing inputs for change analysis and migration generation.
Track LLM API costs in real-time across multiple providers. Monitor token usage, spending limits, budget alerts, and cost attribution per job or task.
Automatic LLM provider failover with fallback chains, inspired by OpenClaw/ZeroClaw model configuration.