Score a repository's agentic legibility from repo-visible evidence only. Use when Codex needs to audit how easy a codebase is for coding agents to discover, bootstrap, validate, and navigate, especially for harness-engineering reviews, developer-experience audits, repo cleanup, or before/after comparisons after improving docs, tooling, or architectural constraints.
Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, or chat applications. Covers Agent class, state management, callable RPC, Workflows integration, and React hooks. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
Performs initial binary triage by surveying memory layout, strings, imports/exports, and functions to quickly understand what a binary does and identify suspicious behavior. Use when first examining a binary, when user asks to triage/survey/analyze a program, or wants an overview before deeper reverse engineering.
Instructions for rust async await module patterns.
Test locomotion system (slide, snap turn, teleport, jump) against the locomotion example using mcp-call.mjs WebSocket CLI.
Test level system (LevelRoot, LevelTag, default lighting, scene hierarchy) against the poke example using mcp-call.mjs WebSocket CLI.
Debug continuous behavior in WebXR scenes — physics, animations, collisions, game loops, or any real-time interaction that happens too fast for an agent to observe. Uses ECS pause/step/snapshot/diff to freeze time and inspect state frame by frame.
**USE THIS FOR COMPLEX TASKS.** Implements Manus-style file-based planning for multi-step tasks. Creates task_plan.md, findings.md, and progress.md in .agent_cache/<task-name>/. Use when: implementing multiple APIs, refactoring modules, research tasks, or ANY task requiring >5 tool calls.
Guide for searching and exploring external GitHub repositories using the gh CLI. Use this when you need reference implementations, patterns, or code examples from open-source projects to help complete your task.
Expert guidance for deep security investigations. Use this when the user asks to "investigate" a case, entity, or incident.
Atomically update task status across TODO.md and state.json. For standalone use only.
Route commands to appropriate workflows based on task language and status. Invoke when executing /task, /research, /plan, /implement commands.
Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).
This skill should be used when scientists need help with research problem selection, project ideation, troubleshooting stuck projects, or strategic scientific decisions. Use this skill when users ask to pitch a new research idea, work through a project problem, evaluate project risks, plan research strategy, navigate decision trees, or get help choosing what scientific problem to work on. Typical requests include "I have an idea for a project", "I'm stuck on my research", "help me evaluate this project", "what should I work on", or "I need strategic advice about my research".
Post-process LaTeX project prose to improve readability through varied sentence and paragraph lengths. Removes filler phrases and unnecessary transitions while preserving all citations and semantic meaning.
Write LaTeX ML/AI review articles for arXiv using the IEEEtran template and verified BibTeX citations.
Personalize COG for your workflow - creates profile, interests, and watchlist files with guided setup (run this first!)
Agentic Workflow Pattern
This skill provides guidance for training FastText text classification models with constraints on accuracy and model size. It should be used when training fastText supervised models, optimizing model size while maintaining accuracy thresholds, or when hyperparameter tuning for text classification tasks.
Upgrade any skill to v5 Hybrid format using decision theory + modal logic