by Evianis · Codex Skill · ★ 749
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git clone https://github.com/Evianis/travel-photo-abstraction.gitTaken from the project's README on GitHub. Check the security audit before running it.
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.
One of 12 tools we ran end to end on the same task for our OpenAI Codex Skills page (2026-10-11).
Result: the agent opened it 15 of 18 times it should have · in Codex with 500 other skills installed: 0 of 3 · in Claude Code with 500 others: 3 of 3
| Stars | 749 |
| Forks | 52 |
| Language | Python |
| Category | Codex Skill |
| Quality Score | 54/100 |
| Open Issues | 2 |
| Last Updated | 2026-08-03 |
| Created | 2026-08-02 |
| Platforms | codex, python |
| Est. Tokens | ~13k |
Travel Photo Abstraction Skill A Codex skill that analyzes a travel or everyday photograph as a visual system, then turns its most distinctive shapes, counts, positions, proportions, colors, directions, depth, and spatial rhythm into a sparse editorial abstraction. The repository includes the bundled reference library used by the skill and a separate set of watermarked showcase outputs.
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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: