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Found 5,656 Skills
Performance analysis coordination workflow. Guides profiling delegation, bottleneck classification (compute/memory/launch/communication/sync), and structured report generation. Use when the user asks to analyze performance, profile a workload, check MFU/SOL, or diagnose bottlenecks.
Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code.
Build local-first executive assistant workflows with OpenClaw for data intake, operational memory, and communications triage
Use when writing or modifying Python code that imports `genoray` to read genotypes/dosages from VCF, PGEN, or SparseVar (`.svar`) files. Covers the public API surface, mode constants, range queries, chunking, filtering, and the SparseVar workflow. Skip for unrelated bioinformatics work.
Use when the user asks to audit what's wrong with a project, "make it right", "看看项目出了什么问题", "为什么用户的需求还没上线", "为什么没提交App Store", "为什么没新build", or wants a holistic state-of-the-project check covering unmerged branches, stalled PRs, failed GitHub Actions, stale builds, plan drift (TODOS.md / ROADMAP), unreleased commits, and log errors. Runs read-only investigation, presents a grouped checklist, fixes only after explicit user confirmation. Aware of the Cathier iOS app workflow (Xcode + fastlane + auto-merge @claude PRs from in-app feedback).
Executes full-project QA like a real user by discovering the repository verification contract, running build, lint, test, and startup commands, exercising core workflows end-to-end, creating realistic fixtures when needed, fixing root-cause regressions, and rerunning the full gate. Use when validating a branch, release candidate, migration, refactor, or risky commit. Do not use for static code review only, one-off unit test edits, or architecture brainstorming without execution.
Interface with Gitea instances via the tea CLI. Manage repositories, issues, pull requests, releases, labels, milestones, CI/CD actions, webhooks, organizations, and notifications. Use when user mentions "Gitea", "tea CLI", or asks to create/list/edit/close issues, create/review/merge pull requests, manage repos, create releases, view CI/CD workflow runs, manage webhooks, track time, or perform any code hosting task on a Gitea server. Do NOT use for GitHub (use gh CLI) or GitLab.
Emergency fix workflow that bypasses normal sprint processes with a full audit trail. Creates hotfix branch, tracks approvals, and ensures the fix is backported correctly.
Build, scaffold, extend, deploy, and troubleshoot event-driven AI agents and scheduled serverless agent apps on Azure Functions using azurefunctions-agents-runtime. Use when the user wants a scheduled agent, morning briefing, daily digest, timer agent, inbox summary, email or Teams briefing, background AI workflow, connector-triggered agent, event-driven AI automation, HTTP/chat agent, webhook-style agent, or Azure Functions hosted agent. Covers .agent.md, agents.config.yaml, Foundry gpt-4.1/gpt-5.x model choice, dynamic sessions for code execution and web browsing, built-in chat/API/MCP endpoints, remote MCP servers, Connector Namespaces, Office 365 or Teams MCP tools/triggers, custom Python tools, Agent Skills, azd deployment, local.settings.json, Application Insights, local development, and troubleshooting.
Use when the user wants to set up, scale, validate, or harden NVIDIA physical AI infrastructure for synthetic data generation workflows across local MicroK8s or Azure AKS, including Kubernetes clusters, inference endpoint deployment, OSMO deployment, workload submission readiness, and infrastructure failure recovery. Trigger keywords: physical ai infrastructure, resilient scaling, SDG infrastructure, microk8s, azure aks, NVCF deployment, NIM Operator, OSMO deploy, workflow scaling. Don't trigger for: OSMO log summarization or workload-only operations unless infrastructure setup, scaling, validation, or recovery is requested.
Execute Python code in isolated rootless containers with MCP server proxying for token-efficient agent workflows
Use when the user asks to "create a metric", "write a metric", "design a metric", "build a metric for", "evaluate agent performance", "measure call quality", "track a KPI", "add a workflow metric", "improve my metric", "fix a metric", "debug metric results", "set up quality scoring", or "what metrics do I need". Also relevant when discussing LLM judge prompts, custom code metrics, evaluation triggers, VALID_SKIP patterns, section extraction, or metric best practices for Cekura voice AI agents. Covers both creating new metrics and reviewing, iterating on, or troubleshooting existing ones.