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Found 9,903 Skills
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for kernel attack surface, namespace and cgroup boundaries, container isolation assumptions, syscall paths, and escape primitive verification. Use when the user asks to analyze container-to-host escape paths, kernel exploit prerequisites, namespace crossover, capability misuse, or prove whether an exploit primitive crosses the sandbox boundary. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
Implement Syncfusion WinUI Funnel Chart (SfFunnelChart) for visualizing data across stages in a process or workflow. Use this when working with funnel charts, conversion funnels, sales pipelines, or process stage analysis in WinUI applications. This skill covers stage-based metrics, hierarchical data representation with decreasing values, and visual representation of progressive reduction in data values across sequential stages.
Parse et explique les messages HL7 v2.5 IHE PAM (Patient Administration Management). Identifie le type de message, extrait les segments (MSH, EVN, PID, PV1, PV2), valide la structure et fournit des explications détaillées des messages ADT pour les workflows d'administration des patients.
Execute a complete tax-loss harvesting workflow from candidate identification through post-harvest monitoring. Use when the user asks about finding TLH candidates, gain/loss budgeting, replacement security selection, wash-sale compliance, or harvest execution planning. Also trigger when users mention 'unrealized losses in my portfolio', 'swap ETFs for tax purposes', 'harvest losses before year-end', 'substantially identical security', 'wash-sale window', 'NIIT offset', 'loss carryforward', or ask how much tax they can save by harvesting.
Rslib best practices for config, CLI workflow, output, declaration files, dependency handling, build optimization and toolchain integration. Use when writing, reviewing, or troubleshooting Rslib projects.
CodeREADr integration. Manage data, records, and automate workflows. Use when the user wants to interact with CodeREADr data.
Use this skill when a user asks to review a pull request for bugs, wants AI code review focused on correctness issues, or runs /bug-review. Trigger on PR review, bug finding, code review, "review this PR", "check for bugs", "find issues in this PR". This is a multi-pass review workflow with 5 parallel passes, majority voting, independent Opus validation, and resolution rate tracking. Also trigger on /bug-review:resolve to classify whether findings were fixed at merge time, and /bug-review:report for resolution rate stats. Even if the user just says "review this" while on a PR branch, trigger this skill.
Loggly integration. Manage data, records, and automate workflows. Use when the user wants to interact with Loggly data.
Infrastructure as code with OpenTofu (open-source Terraform fork) and Pulumi. Covers OpenTofu HCL syntax, providers, resources, data sources, modules, state management with remote backends, workspaces, importing existing infrastructure, plan/apply workflow, variable management, output values, provisioners, and state encryption (OpenTofu-exclusive). Includes Pulumi TypeScript/Python SDKs, stack management, component resources, config/secrets, state backends, policy as code, and automation API. Common patterns for multi-environment setups, module composition, CI/CD integration, drift detection, and secret management. Use when writing or reviewing HCL configurations, managing cloud infrastructure state, migrating from Terraform to OpenTofu, building Pulumi programs in TypeScript or Python, setting up multi-environment IaC pipelines, or implementing state encryption.
Setup and workflow for using sqry semantic code search as an MCP server with Gemini CLI. Covers installation, MCP configuration via settings.json, context file behavior, and recommended patterns. Install this skill to give Gemini CLI access to sqry's 34 AST-based code analysis tools.
Work with Dynatrace notebooks - create, modify, query, and analyze notebook JSON including sections, DQL queries, visualizations, markdown documentation, and analytics workflows. Supports notebook creation from scratch, section-based updates, data extraction from Document Store, structure analysis, investigation workflows, and collaborative documentation.
Early-access skill for Mimiry's softlaunch GPU compute platform. Use this skill whenever the user wants to run a GPU job, start a compute session, train a model, launch a container on a GPU, check their balance, manage running sessions, or build a compute job script on the Mimiry softlaunch environment. Also triggers when the user mentions Mimiry softlaunch, Mimiry compute, GPU sessions, SSH-ing into a session, or asks to "run this on a GPU" or "launch a training job". Covers both quick one-liners and interactive job-building workflows. This is the softlaunch (early beta) version — the API and features may change.