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 Morningstar202604/awesome-skillkit --skill video-generationgit clone --depth 1 https://github.com/Morningstar202604/awesome-skillkitWrote 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/morningstar202604/awesome-skillkit/video-generation)<a href="https://agentmods.dev/skills/morningstar202604/awesome-skillkit/video-generation"><img src="https://agentmods.dev/badge/skills/morningstar202604/awesome-skillkit/video-generation/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/morningstar202604/awesome-skillkit/video-generation"><img src="https://agentmods.dev/badge/skills/morningstar202604/awesome-skillkit/video-generation.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 | $0.00096 | $0.01286 |
| Opus 5 | $0.00048 | $0.00643 |
| Sonnet 5 | $0.00019 | $0.00257 |
| Haiku 4.5 | $0.00010 | $0.00129 |
Grade A, and why
video-generation scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
compatibility: Requires curl and network access to the generation gateway endpoint. How it starts
The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video Generation (text-to-video / image-to-video)
Drive a local generation gateway with curl: submit a task, poll until done, download the result, hand the file path to the user. No ffmpeg, no Python media stacks, no dependency installs — the gateway renders, you orchestrate.
Inputs
| Input | Required | Default | Notes |
|---|---|---|---|
| topic / 文案 | yes | — | what the video shows; user text or a one-line brief |
| aspect_ratio | no | 16:9 |
16:9 landscape, 9:16 vertical, 1:1 square |
| duration | no | 6 |
seconds; 6 or 10 |
| size | no | 720P |
720P or 1080P |
| reference_image_url | no | — | switches mode to image-to-video |
If any required input is missing, ask ONCE, filling defaults for the rest:
请提供：① 视频主题或文案。可选告知：② 画面比例（默认 16:9）、③ 时长 （默认 6 秒，可选 10）、④ 画质（默认 720P）、⑤ 参考图 URL（有则走图生视频）。
Preflight self-check
Run before anything else (BASE comes from step 1 of the workflow):
curl -s -o /dev/null -w "%{http_code}" --max-time 5 "$VIDEO_GATEWAY_BASE/api/video/status?task_id=0"
Expected: any HTTP code printed (gateway reachable). If curl fails to connect (exit != 0): tell the user the gateway is unreachable at $VIDEO_GATEWAY_BASE, ask them to start it, and STOP. Do not fall back to local rendering tools.
Workflow
Step 1: Resolve the gateway base
VIDEO_GATEWAY_BASE="${VIDEO_GATEWAY_BASE:-http://127.0.0.1:30080}"
echo "$VIDEO_GATEWAY_BASE"
Expected: prints one URL. If empty after expansion, the shell is broken — stop.
Step 2: Compose the prompt
Build ONE descriptive paragraph covering action, scene, and mood. Follow the
formula in references/prompt-recipes.md (read it whenever the brief is thin
or the user cares about quality). Never send a bare noun phrase as the prompt.
Step 3: Submit the generation task
Text-to-video:
curl -s -X POST "$VIDEO_GATEWAY_BASE/api/video/generate" \
-H "Content-Type: application/json" \
-d '{"prompt":"<STEP-2 PROMPT>","params":{"aspect_ratio":"16:9","duration":"6","size":"720P"}}'
What ships with it
1 file 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.
- 10d ago First seen · 126 lines · 96 tokens per session scan A f9e55bb38fbe
video-generation is a skill published in the GitHub repository Morningstar202604/awesome-skillkit (1 stars, last pushed today), licensed Apache-2.0. It adds 96 tokens to every session and 1,286 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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