Results for “definition-of-ready”

Guides users to install and run the ai-ready skill for making repositories AI-ready with AGENTS.md, instructions, and CI workflows.

Run an AI-readiness assessment on the current repository and generate a static HTML dashboard at reports/index.html.

Coordinate the end-to-end pipeline from CAD or source assets to SimReady USD assets, including conversion, material and physics assignment, validation, conformance, and optional packaging.

Use this when reviewing whether an app, service, worker, CLI, or serverless system is ready for its target environment with respect to config, secrets, migrations, dependencies, observability, rollback, and runtime constraints.

Audits a codebase for production readiness using local evidence, scoring ship/block risk and listing concrete fixes without sending repo data to external services.

Build production-ready systems with stability patterns: circuit breakers, bulkheads, timeouts, and retry logic. Use when the user mentions "production outage", "circuit breaker", "timeout strategy", "deployment pipeline", "chaos engineering", "bulkhead pattern", "retry with backoff", or "health checks". Also trigger when designing resilient microservices, planning zero-downtime deployments, or investigating cascading failure scenarios. Covers capacity planning, health checks, and anti-fragility patterns. For data systems, see ddia-systems. For system architecture, see system-design.

Audits local code for production readiness, identifying risks in security, data integrity, payments, operations, and UX before shipping.

Design, deploy, and operate production-ready software with stability patterns, capacity planning, and zero-downtime releases.

Deploy trained machine learning models as production-ready services using REST APIs, containers, serverless functions, and orchestration platforms. Use when the user requests model deployment or provides relevant inputs for this workflow.

Generates AI-ready context files for any codebase by auto-detecting the tech stack, scoring AI-readiness, and producing a portable .faf file that works across AI tools.

Provides a sandboxed execution environment for running code snippets, automating tasks, and deploying logic across multiple languages with resource capping and network isolation.

Scaffolds a per-task verification skill for a repo, including a dev-local launcher, a browser driver, and a verification SOP that spawns a sub-agent to drive the app and produce proof.

AI 3D model generation agent. Generates text-to-3D and image-to-3D code (Python/JS/OpenSCAD) using Meshy, Tripo, Hunyuan3D, Rodin, Sloyd, and Stability APIs. Handles game pipeline integration, LOD, retopology, UV, and QC validation.