Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add shaomingchan/whiteboard --skill whiteboard-video-workflowgit clone --depth 1 https://github.com/shaomingchan/whiteboardWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/shaomingchan/whiteboard/whiteboard-video-workflow)<a href="https://agentmods.dev/skills/shaomingchan/whiteboard/whiteboard-video-workflow"><img src="https://agentmods.dev/badge/skills/shaomingchan/whiteboard/whiteboard-video-workflow/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/shaomingchan/whiteboard/whiteboard-video-workflow"><img src="https://agentmods.dev/badge/skills/shaomingchan/whiteboard/whiteboard-video-workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00056 | $0.00403 |
| Opus 5 | $0.00028 | $0.00201 |
| Sonnet 5 | $0.00011 | $0.00081 |
| Haiku 4.5 | $0.00006 | $0.00040 |
Grade A, and why
whiteboard-video-workflow scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Whiteboard Video Workflow
Prefer skills/auto-whiteboard-video for normal end-to-end requests. Use this Skill only for stage-level diagnostics or custom SRT workflows.
Environment
Provider configuration lives in the ignored .env beside this file. Create it through scripts/configure_keys.py; do not edit or print secrets during routine runs.
Supported image providers are apimart_image2, kie_image2, t8_image2, and macode_image2.
Components
scripts/generate-storyboard.py: createstoryboard.jsonfrom subtitles and scene groups.scripts/workflow_helper.py: create output directories, build prompts, and merge segments.scripts/generate-image.py: generate source images with the configured provider.scripts/banana_prompt_template.py: enforce the locked whiteboard drawing style.references/storyboard-parser.md: storyboard rules.references/image-generator.md: image-provider workflow.
Invariants
- Keep scene, image, duration, and video arrays in identical order.
- Treat durations as integer milliseconds across the whole pipeline.
- Request near-16:9 source images and reject clear 3:2, square, and portrait responses.
- Normalize accepted images to the flat
#F6F1E3background before animation. - Use abstract faceless circular-headed people; text must remain sparse and secondary to drawings.
- Preserve cached outputs unless a fingerprint changes or a force flag is explicitly requested.
Stage-Level Validation
Run the repository doctor before troubleshooting. After a custom stage run, verify the expected file count and inspect any JSON manifest before continuing to the next stage.
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- .env.example 1.3 KB
- references/image-generator.md 2.6 KB
- references/storyboard-parser.md 9.6 KB
- scripts/banana_prompt_template.py 2.5 KB runs code
- scripts/check_env.py 4.2 KB runs code
- scripts/generate-image.py 42 KB runs code
- scripts/generate-storyboard.py 8.1 KB runs code
- scripts/workflow_helper.py 7.8 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 37 lines · 56 tokens per session scan A b8fd3756ed23
whiteboard-video-workflow is a skill published in the GitHub repository shaomingchan/whiteboard (49 stars, last pushed 1mo ago), licensed MIT. It adds 56 tokens to every session and 403 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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