higgsfield-claude-skills: 19 Claude Code skills for Higgsfield AI — automate image generation, Seedance 2.0 video creation, and full UGC

Security audit verdict: SAFE · quality 62/100

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. Full audit →

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.

Quick Facts

About higgsfield-claude-skills

Claude Code + Higgsfield — The Complete UGC Pipeline Automate AI image generation, Seedance 2.0 video creation, and full UGC ad pipelines with Playwright browser automation. 19 ready-to-use skills. Quick Install Paste this into Claude Code: That's it. Claude handles the rest. When it finishes you'll have 19 slash commands ready to use.

Compatible Skills

These tools work well together with higgsfield-claude-skills for enhanced workflows:

• browserclaw — semantic(0.19)+complementary+shared_fw(anthropic,playwright)+similar_pop+shared_platform (63%)
• playwright-skill — semantic(0.16)+complementary+shared_fw(anthropic,playwright)+similar_pop+shared_platform (62%)
• jarvis-assistant-vocal — semantic(0.16)+complementary+shared_fw(anthropic,playwright)+similar_pop+shared_platform (61%)
• MCP-Server-Playwright — semantic(0.31)+complementary+shared_fw(playwright)+similar_pop+shared_platform (59%)

higgsfield-claude-skills alternative? Top 4 similar tools

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How this security grade is produced

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:

• SlowMist agent-security taxonomy
• Liu et al., An Empirical Study of Agent Skill Security (2026)
• Our census dataset (DOI 10.5281/zenodo.21292799) · Hugging Face mirror
• How we grade: all 42 rules, the source tiers and known limits
• Full methodology & who runs this