by jin-s13 · Claude Skill · ★ 52
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/jin-s13/ai-research-writing-skill.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.
| Stars | 52 |
| Forks | 7 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 66/100 |
| Last Updated | 2026-10-18 |
| Created | 2026-05-26 |
| Platforms | claude-code, cli, codex, gemini, python |
| Est. Tokens | ~16k |
AI Research Writing Skill 中文说明 Turn an ML/AI research repo into an evidence-backed, build-ready conference paper draft. Point your coding agent at code, experiment logs, notes, and a venue template. This skill helps it produce an auditable LaTeX draft and submission package: story, claim-evidence map, verified citations, figures, reviewer-style critique, rebuttal risks, and build notes.
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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: