video-workbench/AGENTS.md

Video Workbench Agent Rules

Text Encoding

All local project documents are UTF-8 unless a file explicitly declares another encoding.

When reading Markdown, JSON, YAML, text, handoff, prompt, or discussion files from PowerShell, use explicit UTF-8 by default:

Get-Content -LiteralPath <path> -Encoding UTF8
Select-String -Path <path> -Pattern <pattern> -Encoding UTF8

When writing text files, preserve UTF-8. Do not rely on PowerShell encoding defaults for Chinese Markdown.

CCPE Interface

The default external CCPE entrypoint is:

C:\Users\wangq\Documents\Codex\ccpe-system\Interface.md

For CCPE setup or invocation work, read that file first, then follow it to:

C:\Users\wangq\Documents\Codex\ccpe-system\runtimes\hybrid\ccpe-agent-consumer-setup.md

Do not hardcode old Agent, Lite, Skill, Runtime, or protocol paths as default CCPE entrypoints. Read narrower CCPE artifacts only when the consumer setup contract, a project-local registry, or the active task requires them.

Formal CCPE participant output requires a project-local registry, an invocation packet, a real participant carrier, and returned output saved only after the participant returns. Main-session roleplay is not formal CCPE output.

Image Prompt Workflow

All image-generation prompts in this repository must be produced through the gpt-image-2 Skill workflow. Do not draft final image prompts directly from memory or from a derived project skeleton alone.

Before writing any project-bound image prompt, run the Skill mode check and follow the resulting mode:

node C:\Users\wangq\.agents\skills\gpt-image-2\scripts\check-mode.js --json

• Mode A: use the Skill's Garden generation/edit scripts and save prompt/image traces under garden-gpt-image-2/.
• Mode B: use the Skill as a prompt-engineering workflow, save the rendered prompt, then pass it to the host image tool only after user approval.
• Mode C / Advisor: use the Skill as a high-quality prompt advisor, save the rendered prompt, and do not claim an image was generated.

Current default success path for project-bound image generation:

1. Generate the final prompt/spec with the gpt-image-2 Skill Advisor workflow.
2. When image references are needed, load the real reference image into the conversation context before generation.
3. Use the host image_gen tool with the loaded reference image assigned an explicit role such as Image 1.

Use this successful channel now and for future work. Do not switch normal Video Workbench image generation to API/Garden paths unless the user explicitly changes this policy.

For every project-bound image prompt document:

• Read the relevant gpt-image-2 Skill template or reference file before drafting.
• Record the Skill mode, template/reference path, and source files actually read.
• Treat accepted intake/ files and user-provided references as primary sources; use derived files such as visual-system.md, execution-plan.md, or slides/slides.md only as execution control summaries.
• If a prompt was drafted without the Skill workflow, label it as a non-generation-ready draft and rebuild it through the Skill before any image generation.
• When a local image outside the workspace is used, label its role explicitly as identity reference, edit target, or supporting reference, and do not proceed if the file cannot be read or approved.
• For near / identity-heavy shots, prefer a relevant crop reference. For distant / landscape-led shots, prefer the accepted anchor board or project-approved distant reference. Do not repeatedly re-ask whether references can work; the verified route is Skill Advisor prompt plus loaded reference image plus host image_gen.

Project-bound image generation must remain approval-gated: save the prompt/spec first, wait for user approval, then execute generation only when explicitly requested.