For Codex
Last updated July 11, 2026
Codex is strong at code and terminal work.
It still needs image, video, and vision tools.
Watch Codex install AnyCap from a natural-language prompt — skill discovery, CLI setup, authentication, and first image generation in one uninterrupted flow.
Codex is excellent at code, reasoning, and terminal execution. The gap appears when the workflow needs image, video, audio, or visual-analysis capabilities, like product visuals, walkthrough videos, screenshot understanding, or recording review — none of those are Codex tools today.
After adding the AnyCap skill, just tell Codex what you need in plain language. It reads the skill, installs the CLI, authenticates, and calls the right capability — all inside its own terminal session, without any manual setup from you.
One skill. Natural-language install. Immediate capabilities.
Choose a video task
What should Codex do next?
Choose the path that matches the next Codex step. Commands use current AnyCap CLI syntax, while the JSON snippets show representative rather than exhaustive response fields. The 20-credit generation totals are illustrative and vary by model and output settings; every successful video-read request costs a fixed 10 credits.
Generate video from a text brief
Create a new video clip directly from a scene description in the Codex terminal.
Command
anycap video generate --model <model-id> --mode text-to-video --prompt "a short product walkthrough with a slow camera push-in" -o codex-demo.mp4
Result
{
"status": "success",
"local_path": "/workspace/codex-demo.mp4",
"model": "<model-id>",
"credits_used": 20,
"request_id": "req_abc123"
}Additional successful output fields
The JSON above is representative. When available, the CLI may also include:
urltask_idtrace_idhint- Best when
- A new clip should start from a scene you can describe in words.
- Not a fit when
- You need a manual timeline editor or deterministic frame-level control.
Turn an image into video
Animate an existing still while preserving its starting composition or identity.
Command
anycap video generate --model <model-id> --mode image-to-video --prompt "animate this product frame with subtle camera movement" --param images=./product-frame.png -o animated-frame.mp4
Result
{
"status": "success",
"local_path": "/workspace/animated-frame.mp4",
"model": "<model-id>",
"credits_used": 20,
"request_id": "req_def456"
}Additional successful output fields
The JSON above is representative. When available, the CLI may also include:
urltask_idtrace_idhint- Best when
- Composition or identity must begin with an existing still.
- Not a fit when
- The selected model lacks image-to-video support or the still is not ready.
Analyze an existing video
Turn a recording into grounded findings and a useful next step inside the same task.
Command
anycap actions video-read --file ./recording.mp4 --instruction "Summarize the key events, QA findings, and recommended next action"
Result
{
"status": "success",
"content": "The recording shows the checkout modal clipping its submit button on a narrow viewport.",
"credit_cost": 10,
"request_id": "req_ghi789"
}Additional successful output fields
The JSON above is representative. When available, the CLI may also include:
trace_id- Best when
- A recording must become QA notes, extracted content, or a next action.
- Not a fit when
- You need a fixed typed schema for scenes or events.
Get started
Add the skill once.
Then just ask Codex in natural language.
The only bootstrap step is adding the AnyCap skill. After that, you can just tell Codex what to do in plain language. Codex reads the skill, installs the CLI, authenticates, and starts delivering results in the same terminal session without extra setup from you.
Run once
npx -y skills add anycap-ai/anycap -a codex -y
This teaches Codex how to discover and call the AnyCap runtime without changing the way you already work.
Prefer to install manually? Here are the three steps.
Step 1
Install the skill
npx -y skills add anycap-ai/anycap -a codex -y
This teaches Codex how to discover and call the AnyCap runtime.
Step 2
Install the CLI
curl -fsSL https://anycap.ai/install.sh | sh
The CLI is a single binary with no runtime dependencies — it runs inside the Codex sandbox as a standard terminal tool.
Step 3
Log in and verify
anycap login && anycap status
After authentication, Codex can move across image, video, and vision capabilities without new credentials or dashboard detours.
For a full walkthrough, see the install guide.
Why it fits
Built for the way Codex already works
AnyCap installs cleanly into Codex because it was designed for the same constraints: sandboxed VMs, terminal-only output, and ephemeral task environments.
Sandboxed execution
Codex runs each task in an isolated cloud VM. The AnyCap CLI is a dependency-free binary that installs and authenticates inside that sandbox, so no host-level setup leaks between tasks.
Terminal-native output
Codex has no GUI — every result is text in a terminal. AnyCap returns file paths and CDN URLs that Codex can pass to subsequent steps, embed in markdown, or hand off to downstream tooling.
One credential, every capability
Without a runtime layer, adding image generation, video generation, and vision means three separate provider credentials per sandbox. AnyCap consolidates them into one login that covers the full stack.
Capability gap
What you get after those three commands
Codex stays focused on code and terminal execution while AnyCap fills the generation, analysis, search, storage, and publishing gaps that sit outside its sandboxed surface area.
| Capability | Codex alone | Add with AnyCap | Best next step |
|---|---|---|---|
| Image generation | No image output from sandbox | Generate visuals and mockups via anycap image generate | Image Generation page |
| Video generation | No video tooling in terminal loop | Create walkthroughs and clips via anycap video generate | Video Generation page |
| Image understanding | No unified vision runtime | Read screenshots, diagrams, and visual references | Image Understanding page |
| Video analysis | Requires separate provider per task | Inspect recordings from the same CLI | Video Analysis page |
| Audio understanding | No unified audio analysis runtime | Transcribe and analyze audio through one runtime | Audio Understanding page |
| Web search | Search depends on external tooling | Search the web from the same capability layer | Web Search page |
| Grounded web search | No grounded search flow in terminal loop | Run grounded search when the answer needs citations | Grounded Web Search page |
| Web crawl | No reusable crawl runtime | Crawl pages and extract content from one CLI | Web Crawl page |
| Drive storage | No shared asset storage layer | Store outputs with public URLs in AnyCap Drive | Pricing page |
| Page hosting | No built-in page publishing surface | Publish simple pages through AnyCap Page | Pricing page |
| One auth flow | Fresh credential setup per sandbox | One login across the capability stack | Get Started page |
Start with the first missing capability
Creative output
Image Generation
Best next page when Codex needs visuals, mockups, launch assets, or other image output.
anycap image generate
Motion output
Video Generation
Best next page when Codex needs demos, walkthroughs, or short-form video output.
anycap video generate
Vision
Image Understanding
Best next page when Codex needs to interpret screenshots, diagrams, OCR, or design feedback.
anycap actions image-read
Analysis
Video Analysis
Best next page when Codex needs to inspect recordings and extract structured details.
anycap actions video-read
Then pick the model that matches the terminal job
Codex tasks often turn into model-comparison questions once the capability is in place. The common image decision is Seedream 5 vs Nano Banana 2, while video decisions usually become Veo 3.1 vs Kling 3.0. These model pages help Codex choose before it generates anything.
Image model
Seedream 5
Best first-pass image model when Codex needs a polished output from a prompt inside the sandbox.
Compare with Nano Banana 2 when the task is speed vs polish.
Image model
Nano Banana 2
Best for fast iteration when Codex needs more variants, more drafts, or more throughput from image generation.
Compare with Seedream 5 and Nano Banana Pro for workflow tradeoffs.
Video model
Veo 3.1
Best premium video model for Codex when the workflow needs a cleaner cinematic first pass.
Compare with Kling 3.0 and Seedance 1.5 Pro for motion style and production fit.
FAQ
Can Codex generate images on its own?
No. Codex focuses on code reasoning and terminal execution inside a sandboxed VM. It has no built-in image generation runtime. AnyCap adds that capability through one skill install and one CLI, so Codex can produce visuals without leaving its terminal-first workflow.
Why use AnyCap instead of wiring providers directly?
Codex tasks run in isolated, ephemeral cloud sandboxes. Wiring a separate image API, a video API, and a vision API into every task means repeated credential setup and SDK installation. AnyCap consolidates those into one CLI and one login that persists across Codex sessions.
Does AnyCap replace Codex?
No. AnyCap is not an agent. It is a capability runtime that runs alongside Codex. You keep Codex for code, planning, and terminal execution, and add the image, video, and vision tools it does not ship with.
What is the fastest path to add tools to Codex?
Add the AnyCap skill once, then describe what you need in natural language. Codex reads the skill, installs the CLI, authenticates, and calls the right capability automatically. If you prefer manual control, you can also install the CLI and log in yourself in three steps.
Does AnyCap work inside the Codex sandbox?
Yes. The AnyCap CLI is a single binary with no external dependencies. It runs inside the Codex sandbox, sends API requests to the AnyCap server, and returns file paths or URLs that Codex can use in subsequent terminal steps.
Which image model fits Codex best: Seedream 5, Nano Banana 2, or Nano Banana Pro?
For Codex, Seedream 5 is the stronger model when the task needs a polished first-pass result, Nano Banana 2 is better for faster iteration and batch-style generation, and Nano Banana Pro is the better fit when Codex needs targeted edits to an existing image.
Which video model fits Codex best: Veo 3.1, Kling 3.0, or Seedance 1.5 Pro?
For Codex, Veo 3.1 is the premium default, Kling 3.0 is a stronger fit for more cinematic motion, and Seedance 1.5 Pro is a steadier choice for repeatable image-to-video production workflows.
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Last updated Apr 2026