skill to create best prompts for generating videos with seedance2.0
2.7k
Stars
270
Forks
0
Open issues
1
Contributors
AI Analysis
A specialized skill resource for writing effective video generation prompts for ByteDance's Seedance 2.0 AI model, integrated with agent platforms like Claude Code and Cursor. It provides prompt structure patterns, syntax references, and templates for specific use cases (ads, dramas, MVs, educational content). This tool is designed for content creators and AI agents working specifically with Seedance 2.0; it is not a general-purpose prompt engineering resource.
Inferred from signals mentioned in the README (tests, CI, type safety) — not a review of the actual code.
AI's overall editorial judgment — not an average of the bars above, can weigh other factors too.
Claude agent skill for writing Seedance 2.0 video prompts, designed for AI-assisted prompt engineering
A prompt-engineering skill module for Claude Code, Cursor, and compatible AI agents, designed to help users craft effective video generation prompts for ByteDance's Seedance 2.0 multimodal video model. It bundles documentation on syntax, camera language, templates, and examples. Built for developers and content creators using AI-assisted coding environments. Adoption appears limited to the Seedance ecosystem and emerging AI agent skill market; strong early growth (219 stars in 7 days) reflects recency and niche enthusiasm rather than established production deployment.
Created 2026-02-11, this is a very recent project (4 months old as of evaluation date). It emerged during the rapid adoption of agent skills systems and ByteDance's public release/promotion of Seedance 2.0 capabilities. Built on official ByteDance documentation, positioning itself as a standardized reference for prompt engineering within agent workflows.
Gained 219 stars in the last 7 days alone, indicating viral adoption within a narrow technical community — likely driven by: (1) novelty of AI agent skills market in early 2026, (2) ByteDance's promotion of Seedance 2.0, (3) timing with Claude Code and Cursor ecosystem expansion. However, absolute star count (2,325) and fork activity (238) are modest for a 4-month-old project with high growth rate, suggesting concentrated adoption rather than mainstream penetration.
Adoption not verified. No case studies, quotes, or documented production deployments mentioned in README. The project surfaces 'real-world cases' from ByteDance documentation (drama, ads, education, MVs) but these are Seedance 2.0 examples, not evidence that this specific skill module is in production use. Star and fork counts suggest interest, but do not confirm actual integration into workflows.
Based on README, appears to be a documentation-driven skill module (markdown files: SKILL.md in English and Chinese). No code repository structure is described. Likely consists of structured text guidelines rather than executable algorithms or libraries. Distribution via manual file copy or CLI package manager (npx skills add) suggests a minimal, composable architecture.
Not documented in README. No mention of test suites, validation scripts, or quality gates. Given the documentation-first nature, testing may consist of manual validation against Seedance 2.0 API or user feedback rather than unit tests.
Last push 2026-02-18, just 7 days after creation (2026-02-11). Project is extremely recent and has not yet demonstrated sustained maintenance patterns. No visible issue tracker, pull request history, or deprecation/versioning strategy documented. Too early to assess long-term maintenance reliability.
ADOPT IF: you are actively using Claude Code, Cursor, or compatible agents to generate Seedance 2.0 video prompts and want structured guidance integrated into your workflow; the skill is actively maintained and does not require external dependencies. AVOID IF: you need battle-tested, widely-adopted tooling with clear production case studies and documented reliability; or if you work outside the ByteDance ecosystem; or if you require version stability and long-term support — the project is 4 months old with no versioning or deprecation strategy visible. MONITOR IF: you are building AI agent skill systems for content generation; this project signals where the market is moving, and early adopters may inform better abstraction choices for your own tools.
Independent dimensions
Mainstream potential
3/10
Technical importance
4/10
Adoption evidence
2/10
- Extremely recent creation (4 months old) with no demonstrated long-term maintenance history; may be abandoned or deprioritized post-launch.
- Adoption not verified in actual production environments; star counts may reflect speculative interest rather than real deployment.
- Heavy dependency on ByteDance's Seedance 2.0 API stability and business continuity; no fallback or vendor-agnostic design evident.
- Narrow market scope (Seedance-specific, agent-skill ecosystem dependent); limited to users of Claude Code, Cursor, or compatible agents.
- No documented testing, validation, or quality assurance process; prompt effectiveness not independently verified against edge cases.
Likely to remain a niche, specialized tool within the Seedance 2.0 + AI agent ecosystem. May be adopted as a reference model by other ByteDance product skill developers, but unlikely to achieve mainstream adoption outside video generation workflows. Could be superseded by official ByteDance tooling or consolidated into broader agent skill marketplaces.
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Languages
No language breakdown available.
Information
- Website
- https://seedance2.help
- License
- MIT
- Last updated
- 5mo ago
- Created
- 5mo ago
- Analyzed with
- anthropic/claude-haiku-4-5
Stars over time
Contributors over time
Top 100 contributors only — repos with more will plateau at 100.
Open issues
No open issues — clean slate.
Open pull requests
No open pull requests.
Top contributors
Recent releases
No releases published yet.
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Slightly lower star count (2,021 vs 2,325) and similar recency window; appears to be a direct competitor addressing the same need. Evaluation shows crowded, early-stage market with multiple similar offerings.
Much larger star count (9,975) but broader scope (generic prompt engineering, not Seedance-specific). Different positioning; prompt-master likely targets general LLM users rather than video generation specialists.
Similar focus and lower star count (1,453). Appears to be a curated collection rather than a formalized agent skill. Less structured for integration with AI agents.
Shell-based, 2,019 stars. Likely a broader resource collection rather than a standardized agent skill module. Different format and distribution model.