2.2K skills · sorted by relevance
Choose coding challenges matched to a learner’s level and goals within Flow Nexus. Validate submissions, review solution quality and efficiency, and track progress through rankings, achievements, badges, and challenge completion rewards.
Set up and operate Ruflo to coordinate multiple AI coding agents. This skill guides project initialization, shared memory, task assignment, health checks, and plugin discovery for work that needs coordinated or parallel execution.
Manage Flow Nexus accounts, run code in sandboxes, deploy app templates, and track credits. The skill guides platform operations through connected tools, including file storage, execution monitoring, and coding challenge submissions.
Work with AI as a coding partner, choosing who writes code and who guides the work. Supports role switching, test generation, ongoing code review, debugging, and step-by-step explanations for learning.
Review website JPEGs for progressive encoding, which displays a blurry preview before sharpening. Identify images that could use this format, consider file size and loading behavior together, and explain how to confirm the change in browser developer tools.
Set up ESLint, a tool that checks JavaScript for errors and coding rule violations. Configure shared rules, connect checks to editors and automated workflows, and review flagged code alongside its behavior in the browser.
Check whether HTML, JavaScript, and CSS are delivered with Gzip or Brotli compression. Use measured loading problems and response headers to guide server or CDN changes that reduce the amount of data downloaded.
Study AI engineering through interactive terminal lessons with explanations, coding exercises, and quizzes. The tutor follows your recorded progress, revisits previous material, adapts to your answers, and logs results and topics that need review.
Research a coding task before implementation and turn it into a detailed work plan with decisions, dependencies, and verification steps. The plan is written after approval, while code changes remain a separate workflow.
Manage coding-agent sessions across connected machines through Herdr, tmux, and MSP. See which sessions need attention, review their output, open sessions with a brief, send instructions, answer approval dialogs, and stop or close sessions.
Recover context from local coding-agent transcripts and produce a checkpoint covering the objective, completed work, blockers, and next step. Explicit import requests support read-only recovery, with continuation governed by the current workspace rules and the user's request.
Find facts and data with web search, prioritizing primary or authoritative sources. Record exact figures, units, time periods, and source URLs in shared history so later calculation, coding, or writing can use traceable evidence.
Set up and customize Pi, a terminal coding agent framework. This skill guides model configuration, extension development, terminal interfaces, and integration with other applications through its SDK, a software development kit, or process messaging.
Delegate code analysis and implementation to Codex CLI without an interactive session. The skill reads ordered output events, extracts the final agent response, and reports errors, with a read-only sandbox used by default.
Find context from past coding sessions in Hindsight long-term memory. Reuse memories already loaded for the session, search for missing details, and reason over accumulated records when answering questions about decisions, project context, or preferences.
Control interactive command-line programs through tmux by sending keystrokes, reading terminal output, and waiting for prompts. Use separate sessions to operate Python consoles or run multiple coding agents while checking their progress and results.
Hand a scoped coding task to Aider while the coordinating agent reviews changes, runs project checks, and commits the result. Covers task briefs, execution tracking, and follow-up edits, but the executable helper is not bundled.
Manage coding work from issue intake through implementation, review, deployment, and acceptance checks. Track each completion requirement against fresh evidence, with defined retry limits and explicit escalation when progress needs human input.
Practice an interview tailored to a specific job, with a chosen format and difficulty. Answer one question at a time, handle follow-up questions, and receive scores and improvement suggestions grounded in your answers.
Analyze packet captures in a CTF sandbox by rebuilding communication sessions and decoding message contents. Recover transferred files and connect packet order, timing, and reconstructed streams to observed host or malware behavior.
Recover hidden malware settings and communication parameters in an isolated CTF environment. Document how values are decoded, preserve supporting evidence, and connect recovered fields to the sample’s observed behavior.
Analyze captured network traffic and binary messages to recover custom protocol structures. The skill organizes message types, fields, and connection states, then produces reproducible decoding steps with supporting evidence for authorized investigations.
Review Python code for common mistakes in error handling, asynchronous operations, type annotations, and tests. Use a practical checklist and correction examples to guide code reviews, investigate bugs, and improve existing implementations.
Split multi-step coding, research, or testing into focused assignments for sub-agents, which are agents handling specific parts of a task. The parent agent retains design decisions, integration, and final verification while independent work runs in parallel.