video-character-design

Create character design documentation and character design sheet images for video.

What this skill does for you

Create character design documentation and character design sheet images for video, storyboard, advertising, animation, or AI video-generation workflows. Use this skill whenever the user asks to design a character, extract a character from a reference image, make a character sheet, create a turnaround sheet, keep a person consistent across scenes, or generate character assets for a video project. This skill first writes a confirmable {character-name}.md design spec, waits for user approval or revision, and only then generates {character-name}.png.

Quoted from the skill description in the pinned source

Who made it

Publisheragentara

Repositoryskills

Installs327as of Sep 27, 2026

Use it with Edge

Set up Edge for me: read getedge.cc/SKILL.md and follow it. Then use Edge to load the video-character-design skill from agentara/skills.

Paste it into Claude, ChatGPT, Codex or Cursor.

Or read the skill source first.

Security evidence

Security state at 2026-09-30: reviewed. State definitions. This records static evidence for this revision; live load eligibility is checked again.

3 static scans, 0 counted findings. The listed scanners recorded the results shown for this package revision.

Scanner	Date	Result
Edge static checks	2026-09-27	Pass
Cisco skill-scanner	2026-09-27	Pass
Semgrep Edge rules	2026-09-27	Pass

Static scans check the code, not how well the skill works.

Scanner scope, raw findings and mirrored provider records

Edge static checks (Edge-run): edge-static/1.0.1. Scope: Static patterns for remote execution, credentials with network sends, obfuscation, prompt overrides, hidden Unicode, binaries and persistence. Revision: a529df80920bb3162f91f7df71c03a2abeb66232. Raw findings: . Counted findings: .

Cisco skill-scanner (Edge-run): cisco-skill-scanner/2.1.0. Scope: Local static, YARA, pipeline and behavioral analyzers; no LLM or AI Defense analysis. Revision: a529df80920bb3162f91f7df71c03a2abeb66232. Raw findings: 1. Counted findings: .

Semgrep Edge rules (Edge-run): semgrep/1.178.0+edge-rules.c15016a36fd3+offline-v1. Scope: Six Edge-authored static rules with Semgrep CE; offline execution and metrics disabled. Semgrep-maintained rules excluded. Revision: a529df80920bb3162f91f7df71c03a2abeb66232. Raw findings: . Counted findings: .

Source and licence

Repository: https://github.com/agentara/skills
Pinned skill file: View source at revision
Revision: a529df80920bb3162f91f7df71c03a2abeb66232
Package hash: sha256:5ded1986a2f0e0ab449201abe687d6e8b88a9b3315ced198de831ee74b984981
Licence: MIT