openrouter-text2video

Name: openrouter-text2video
Author: QinghongLin/data2story-skill

$npx mdskill add QinghongLin/data2story-skill/openrouter-text2video

Generate videos from text prompts via OpenRouter using ByteDance Seedance 2.0.

Creates videos from text descriptions for use in projects or assets.
Depends on OpenRouter API and ByteDance Seedance 2.0 model.
Uses async video generation with polling until completion or timeout.
Downloads the resulting MP4 video to a specified file path.

SKILL.md

.github/skills/openrouter-text2videoView on GitHub ↗

---
name: openrouter-text2video
description: Generate videos via OpenRouter using ByteDance Seedance 2.0.
---

# openrouter-text2video

Text → video via OpenRouter. Default model: `bytedance/seedance-2.0`.

Uses the async video-generation endpoint: submit job → poll → download.

## Usage

Resolve `TOOL_DIR` = the directory containing this `SKILL.md`. Commands below use `TOOL_DIR` as a symbolic placeholder; replace it with the resolved, quoted path before running Bash.

```bash
export OPENROUTER_API_KEY=sk-or-v1-...

python3 TOOL_DIR/scripts/generate_video.py \
  --prompt "A slow dolly push through a retro-futuristic arcade, neon signs reflecting in a puddle" \
  --duration 5 \
  --aspect-ratio 16:9 \
  --resolution 720p \
  --download PROJECT_DIR/assets/hero.mp4
```

## Flags

| Flag | Default | Description |
|---|---|---|
| `--prompt` | required | Text prompt |
| `--download` | required | Output MP4 path |
| `--model` | `bytedance/seedance-2.0` | Any OpenRouter video model |
| `--duration` | `5` | Seconds |
| `--aspect-ratio` | `16:9` | `16:9`, `9:16`, `1:1`, `4:3`, `3:4`, `21:9`, `9:21` |
| `--resolution` | `720p` | Model-dependent (e.g. `480p`, `720p`, `1080p`) |
| `--generate-audio` | off | Generate audio with video (if model supports) |
| `--poll-interval` | `5` | Seconds between polls |
| `--max-wait` | `600` | Max total wait time |

## Flow

1. `POST /api/v1/videos` → returns `{id, polling_url, status: "pending"}`
2. `GET /api/v1/videos/{id}` every 5s until `status == "completed"`
3. `GET /api/v1/videos/{id}/content` → raw MP4 bytes

## Pricing

Seedance 2.0: ~$7/M tokens with `(height × width × duration × 24) / 1024` token formula. A 5-second 720p 16:9 clip ≈ 145k tokens ≈ $1.

## Notes

- Supports text-to-video, image-to-video (first/last frame control via `frame_images`), and reference-to-video.
- This script only wires text-to-video. Extend the body to add `frame_images` or `input_references` for advanced modes.

More from QinghongLin/data2story-skill

Skill	Description
analyst	Exhaustively profile a dataset and list ALL possible analyses — distributions, correlations, rankings, trends, group comparisons, anomalies. Reads detective.json for context. Runs after the Detective/Scout, before the Editor. Outputs analyst.json with ana_xx IDs and chart-ready data_tables.
auditor	Audit a generated Data2Story blog for build correctness across ALL modalities by ACTUALLY RENDERING it in a real headless browser (when available) — catching blank/0-width charts, broken/oversized media, desktop+mobile overflow, and dead interactions that source inspection cannot see — then having vision agents review the screenshots, playtesting every interactive, and walking the flagship capability contract. Plus VIEW every image for a wrong/AI-faked subject. Fixes layout in place; sends content-correctness problems back to the owning role. Use at Stage 6 after the Programmer assembles index.html and before the Critic; re-runs each revision round. Triggers: a built index.html exists, or you need to confirm charts/media/interactions actually render.
cinematographer	Design the MANDATORY cinematic scroll experience (every blog ships one): a full-bleed, scroll-driven background — primarily from the Scout's verified real imagery — plus the global motion choreography, so the narrative unfolds like a film as the reader scrolls. Owns the BACKGROUND layer + page-level motion (not the Designer's per-section visuals, not the Interaction centerpiece — it stages them inside the scroll). Outputs cinematographer.json (cin_xx scenes). There is no off path: a topic with no sourceable real imagery falls back to a generative-atmosphere or data-driven-spine background, never to a bare column.
copywriter	Name the piece — re-write the masthead (headline + standfirst + kicker), every section title, and every figure/photo/table caption to a research-driven titling standard, killing the AI-tell patterns (the 'flat statement. flat counter-statement.' two-beat above all) a competent default falls into. Reads editor.md/json + analyst.json + the resolved topic_profile; writes copywriter.json — STRINGS ONLY (masthead{headline,standfirst,kicker}, items{edt_xx:{title}, des_xx:{caption}}), each backed by a real ana_. Names, never edits: it touches no finding, no number, no data- id, no layout — so the Verify layer is untouched and the Programmer renders the masthead + figcaptions from copywriter.json verbatim. Runs at Stage 3.5, after the Editor, before the Designer.
critic	Review a finished Data2Story blog against the 5 quality rubric dimensions (visual_design, narrative_pacing, data_method_transparency, claim_data_alignment, insight_value), score each 1-7 with on-page evidence, and emit critic.json with pass/fail + targeted, surgical send-back instructions. Verifies every load-bearing claim/asset against its traceability chain before scoring; applies the caveat-survival, honest-accuracy, and third-party-attribution caps. Does NOT rewrite content — scores and sends back. Use at Stage 6.5 after the Auditor and after verify.py has produced verifier.json; re-runs each revision round. Triggers: a built index.html plus verifier.json exist, or you need to judge whether the article is actually good.
data2story	Data Journalist Agent (Data2Story) — orchestrator: turn a dataset into a blog. Runs detective → analyst → editor → designer → programmer → auditor → inspector in sequence. Creates a versioned project folder for each run.
data2story-pro	Use to turn a dataset into a verifiable multimedia blog (a data story / data-driven article / interactive dashboard from a dataset). Orchestrator for the Data Journalist Agent (Data2Story): a 7-team newsroom (14 agents) running detective → scout → analyst → imagineer → editor → copywriter → designer → interaction → hero → cinematographer → programmer → auditor → critic → inspector in sequence. Trigger when the user hands over a dataset (CSV/JSON/folder/path) and wants a published story, blog post, or interactive report built from it. Creates a versioned project folder per run.
dataviz-craft	A shared reference library for editorial-grade data-visualization craft — Vega-Lite-first with a D3 fallback for charts Vega-Lite can't express. Read by the Designer at chart selection (intent → ranked chart type), the Programmer at implementation (editorial Vega-Lite recipes, annotation layers, axis/label de-clutter, encoding craft), and the Auditor/Critic for chart-quality review. It encodes the FT Visual Vocabulary intent taxonomy, the Cleveland–McGill channel-accuracy ordering, the BBC bbplot de-clutter ruleset, and colorblind-safe encoding rules. Not a pipeline stage — a craft source, like frontend-design.
designer	Read editor.md, editor.json, and analyst.json. Make data-driven creative visual decisions for every section — teaser, charts, images, videos, audio, maps, and interactive demos when they fit the data. Generate selected assets. No HTML. Outputs designer.json with des_xx IDs.
detective	Research external context for a dataset — domain background, history, related studies, and why this data matters. Outputs detective.json (structured findings with det_xx IDs) before any analysis begins.