by Bria-AI · Claude Skill · ★ 70
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Featured in: Image Generation · Claude Code Skills
npx skills add bria-ai/bria-skill
claude mcp add bria-skills -- npx -y bria-skillsTaken from the project's README on GitHub.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 70 |
| Forks | 7 |
| Language | Python |
| Category | Claude Skill |
| Quality Score | 69/100 |
| Open Issues | 2 |
| Last Updated | 2026-10-21 |
| Created | 2026-02-05 |
| Platforms | claude-code, python |
| Est. Tokens | ~14k |
Bria AI Skills — Controllable Image Generation for Coding Agents Generate, edit, and precisely control images directly from your AI coding agent using Bria.ai's commercially-safe models. Unlike black-box generators, Bria gives you fine-grained control: edit specific objects, mask regions, control lighting/season/style independently, and chain operations in pipelines.
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: