Empire LLM for Codex

empire-benchmarks

Fetch current Artificial Analysis language-model benchmarks, join exact OpenRouter model identities, apply transparent weighted scoring and modality requirements, and render a sandboxed vertical comparison chart in supported Codex or ChatGPT surfaces. Use for current best-model questions, agentic or coding benchmark comparisons, route-fit visualizations, and benchmark-weighted model selection; do not use it to dispatch a model completion.

empire-cost-policy

Resolve and enforce Empire LLM economic boundaries before external-model routing. Use when a user asks for free-only or Absolute Zero models, prefers free or value routing, requests frontier models, sets a spending ceiling or target language, previews a route, asks why a model was chosen, or wants to prevent paid fallback.

empire-handoff

Route one bounded planning checklist or single-file implementation proposal to an external model, quarantine and validate it outside the repository, and let Codex preview, download, adversarially review, approve for consideration, or reject it without automatic application. Use when the user asks for an Empire handoff, external-model implementation proposal, downloadable model artifact, project checklist, single-file frontend, partner plan, or worker file while Codex remains the only repository writer.

empire-image

Route one bounded image-generation or image-edit request to a current non-OpenAI OpenRouter media endpoint, preview and authorize its cost, validate the returned image, and quarantine it outside the repository while Codex remains in control. Use for image prompts, icons, illustrations, transparent assets, image variations, reference-image edits, or an explicit request for Empire image generation.

empire-readiness

Score Empire LLM Codex publishing readiness from 1 to 10 and maintain an evidence-based Codex App Store to-do loop covering engineering, security, live routing, publisher identity, public legal URLs, artwork, submission tests, release state, and real-diff acceptance. Use when the user asks whether Empire is ready, requests a readiness score or checklist, wants the next release step, or asks for the marketplace feedback loop.

empire-review

Route one bounded code review or second opinion to a current non-OpenAI model through OpenRouter, optionally enriched with Artificial Analysis data, while Codex remains the lead worker. Use when the user asks for an Empire review, external model review, routed second opinion, or partner-model critique of a diff or selected files.

empire-settings

Configure, inspect, or remove Empire LLM credentials and project budget settings without exposing secret values. Use when the user asks to set up Empire, enter OpenRouter or Artificial Analysis credentials, check Empire credentials, change the review budget, or sign out.

empire-video

Route one bounded text-to-video or image-guided video request to a current non-OpenAI OpenRouter media model, preview and authorize cost, manage the asynchronous job, validate the MP4, and quarantine it outside the repository while Codex remains in control. Use for video prompts, landing-page loops, image-to-video, reference-guided clips, or an explicit request for Empire video generation.

empire-web-escalation

Research publicly accessible web sources using Codex native web tools, cite the evidence, and report unavailable sources. Use for public documentation lookup, source verification, or public-page research. This skill does not provide a third-party web API or managed browser.