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Found 4,970 Skills
Evaluate AI contribution in projects using the AI Assessment Scale (AIAS) 5-level framework. Measure AI involvement from no AI to full AI exploration across development stages.
Detects .NET intent for any C#, ASP.NET Core, EF Core, Blazor, MAUI, Uno Platform, WPF, WinUI, SignalR, gRPC, xUnit, NuGet, or MSBuild request from prompt keywords and repository signals (.sln, .csproj, global.json, .cs files). First skill to invoke for all .NET work — loads version-specific coding standards and routes to domain skills via [skill:dotnet-advisor] before any planning or implementation. Do not use for clearly non-.NET tasks (Python, JavaScript, Go, Rust, Java).
Teamleader integration. Manage Deals, Persons, Organizations, Leads, Projects, Pipelines and more. Use when the user wants to interact with Teamleader data.
Calendly integration. Manage Users. Use when the user wants to interact with Calendly data.
Use when automating LinkedIn via CLI: fetch profiles, search people/companies, send messages, manage connections, create posts, and Sales Navigator.
Intercom integration. Manage Users, Companies, Conversations, Admins, Tags, Segments and more. Use when the user wants to interact with Intercom data.
Pull latest origin/main into the current local branch and resolve merge conflicts (aka update-branch). Use when Codex needs to sync a feature branch with origin, perform a merge-based update (not rebase), and guide conflict resolution best practices.
Two-way integration channel between Feishu (Lark/Feishu) and OpenClaw. It implements message receiving and sending through Feishu bot, supporting private chat, group chat, @mention detection, card messages, and file transfer. This skill is used when you need to interact with AI assistants via Feishu, receive Feishu messages to trigger AI responses, or send messages from OpenClaw to Feishu. Difference from feishu-automation: this skill focuses on message channel integration, while feishu-automation focuses on automated operations of Feishu platform (such as multidimensional tables, documents, etc.)
Iteratively improve any output until measurable criteria are met. Use when the user wants to refine existing work against specific standards — whether it's code, prose, data, config, or any other artifact. Triggers on phrases like "improve this", "make it better", "iterate", "refine", "keep improving", "not good enough yet", "optimize this", "polish this", "tighten this up", or when the user provides criteria and wants repeated improvement until they're satisfied. Also use when the user gives feedback on output and expects you to keep refining, even if they don't say "improve" explicitly.
Use when the user wants to review a pull request, understand what a PR changes, assess risk of merging, or check for missing test coverage. Examples: "Review this PR", "What does PR #42 change?", "Is this PR safe to merge?"
Arquitecto de Soluciones Principal y Consultor Tecnológico de Andru.ia. Diagnostica y traza la hoja de ruta óptima para proyectos de IA en español.
Interactively create a new Claude Code skill and add it to the elastic-docs-skills catalog. Use when the user wants to generate a new skill, scaffold a slash command, or build automation for docs tasks.