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 cinience/alicloud-skills --skill aliyun-wan-digital-humangit clone --depth 1 https://github.com/cinience/alicloud-skillsWrote 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/cinience/alicloud-skills/aliyun-wan-digital-human)<a href="https://agentmods.dev/skills/cinience/alicloud-skills/aliyun-wan-digital-human"><img src="https://agentmods.dev/badge/skills/cinience/alicloud-skills/aliyun-wan-digital-human/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/cinience/alicloud-skills/aliyun-wan-digital-human"><img src="https://agentmods.dev/badge/skills/cinience/alicloud-skills/aliyun-wan-digital-human.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 14 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00059 | $0.00719 |
| Opus 5 | $0.00030 | $0.00360 |
| Sonnet 5 | $0.00012 | $0.00144 |
| Haiku 4.5 | $0.00006 | $0.00072 |
Grade A, and why
aliyun-wan-digital-human 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 13d 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.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Category: provider
Model Studio Digital Human
Validation
mkdir -p output/aliyun-wan-digital-human
python -m py_compile skills/ai/video/aliyun-wan-digital-human/scripts/prepare_digital_human_request.py && echo "py_compile_ok" > output/aliyun-wan-digital-human/validate.txt
Pass criteria: command exits 0 and output/aliyun-wan-digital-human/validate.txt is generated.
Output And Evidence
- Save normalized request payloads, chosen resolution, and task polling snapshots under
output/aliyun-wan-digital-human/. - Record image/audio URLs and whether the input image passed detection.
Use this skill for image + audio driven speaking, singing, or presenting characters.
Critical model names
Use these exact model strings:
wan2.2-s2v-detectwan2.2-s2v
Selection guidance:
- Run
wan2.2-s2v-detectfirst to validate the image. - Use
wan2.2-s2vfor the actual video generation job.
Prerequisites
- China mainland (Beijing) only.
- Set
DASHSCOPE_API_KEYin your environment, or adddashscope_api_keyto~/.alibabacloud/credentials. - Input audio should contain clear speech or singing, and input image should depict a clear subject.
Normalized interface (video.digital_human)
Detect Request
model(string, optional): defaultwan2.2-s2v-detectimage_url(string, required)
Generate Request
model(string, optional): defaultwan2.2-s2vimage_url(string, required)audio_url(string, required)resolution(string, optional):480Por720Pscenario(string, optional):talk,sing, orperform
Response
task_id(string)task_status(string)video_url(string, when finished)
Quick start
python skills/ai/video/aliyun-wan-digital-human/scripts/prepare_digital_human_request.py \
--image-url "https://example.com/anchor.png" \
--audio-url "https://example.com/voice.mp3" \
--resolution 720P \
--scenario talk
Operational guidance
- Use a portrait, half-body, or full-body image with a clear face and stable framing.
- Match audio length to the desired output duration; the output follows the audio length up to the model limit.
- Keep image and audio as public HTTP/HTTPS URLs.
- If the image fails detection, do not proceed directly to video generation.
What ships with it
3 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.
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.
- 13d ago First seen · 86 lines · 59 tokens per session scan A 1fe65e0f19e1
aliyun-wan-digital-human is a skill published in the GitHub repository cinience/alicloud-skills (396 stars, last pushed 1mo ago), licensed MIT. It adds 59 tokens to every session and 719 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…