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Found 6,606 Skills
Add an in-app feedback and bug-report loop that captures a screenshot plus network/console logs, emails the reporter, launches a Cursor Cloud Agent with autoCreatePr, and emails again when the PR opens and when it merges. Use when asked to add feedback, bug reporting, user reports that open PRs, Cursor automation for feedback, or a feedback-to-PR workflow.
Scan how you actually work with your coding agent and surface what to encode next. Point it at ONE run's artifacts to find what would have prevented a specific failure (the reactive loop — 'that went wrong, what should change in the AI layer?'), or at a window of session logs to find recurring patterns worth building (the proactive scan). Agent-agnostic. Outputs a shape-only HTML report. Use to evolve your system from real usage.
Primes the agent with deep codebase understanding by analyzing structure, documentation, and key files. Use when starting work on a codebase, at the beginning of a session, or when you need a fast orientation before planning or implementing. Optionally pulls external task context from Jira issues and Confluence pages first.
Audit any second brain, notes folder, or agent memory for facts that have quietly stopped being true, then fix the worst one so it stops recurring. Works on a wiki, a single notes file, daily notes, or a non-markdown tool, and adapts the fix to whichever it finds. Checks every current-sounding claim in whatever the agent loads each session against the freshest evidence, and separates contradicted claims from unsupported ones. Use when an assistant gives an outdated answer, when notes or memory files may be stale, when a vault needs checking for contradictions, or when someone asks how to stop a second brain from rotting, mentions memory rot, or asks about state versus event.
Primes the agent with focused understanding of the frontend portion of the codebase — components, routing, state management, and styling — without loading unrelated backend code. Use at the start of a session when the work is scoped to UI or client-side features. Optionally pulls external task context from Jira issues and Confluence pages first.
Discover agent-native CLIs for professional software. Access the live catalog to find tools for creative workflows, productivity, AI, and more.
Submit feedback on an Expo skill—or Expo itself—and control bundled anonymous usage telemetry (off by default / opt-in). Submit feedback with: npx --yes submit-expo-feedback@latest "ACTIONABLE_FEEDBACK". Optionally add either or both: --category "CATEGORY" and --subject "SUBJECT". Replace the uppercase placeholders before running. Use when a skill was useful, confusing, broken, missing context, or worth improving; when Expo, Expo CLI, EAS CLI, docs, or MCP worked well or fell short; when an AI agent repeatedly failed, got stuck, or needed the user to take over an Expo task (report it as an eval candidate); or when the user explicitly asks to enable or disable telemetry (tracking), check its status, or understand what it collects.
Creates, optimizes, and iteratively refines agent prompts, system prompts, developer prompts, and reusable prompt templates. Use when asked to improve a prompt, optimize a system prompt, rewrite an agent prompt, tune prompt wording, make a prompt more reliable, port prompts between OpenAI, Claude, or Gemini, or build prompt evals.
Creates and maintains concise AGENTS.md and CLAUDE.md project instruction files. Use when asked to create AGENTS.md, update AGENTS.md, maintain agent docs, set up CLAUDE.md, document repository agent conventions, or keep coding-agent instructions minimal and reference-backed.
Solve an interactive hidden-rule ARC-AGI-3 game from its game ID. Contains the complete playing doctrine (predict before every action, graded claims, one-page notes, optional executable-rules search) plus the `arc` harness the agent drives. Use whenever asked to solve, play, or continue an ARC-AGI-3 game.
Generate a documentation pack for a .NET repository so AI coding agents can reason about it — AGENTS.md, architecture, ADRs, data model, infrastructure, plus a `docs/dotnet.md` deep-dive covering the solution/project graph, target frameworks, EF Core data access, DI, configuration & secrets, analyzers, and CI. Invoke with `/arkandia:agent-context-dotnet [en|es]`.
Use this skill when you writing commands, hooks, skills for Agent, or prompts for sub agents or any other LLM interaction, including optimizing prompts, improving LLM outputs, or designing production prompt templates.