by tigerless-labs · Claude Skill · ★ 213
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
Feed your agent papers and half-formed ideas — it links them into a system design you can defend. Markdown keeps the record; a visual canvas makes it readable. An Agent Skill for Claude Code & any SKILL.md-compatible agent.
| Stars | 213 |
| Forks | 33 |
| Language | Python |
| Category | Claude Skill |
| Quality Score | 51.5864963013798/100 |
| Open Issues | 2 |
| Last Updated | 2026-09-01 |
| Created | 2026-07-07 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~13k |
Looking for a design-harness alternative? If you're comparing design-harness with other claude skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
做证据可信、过程可追、自主优化的长程自动化 AI 科研工具。
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design-harness is Feed your agent papers and half-formed ideas — it links them into a system design you can defend. Markdown keeps the record; a visual canvas makes it readable. An Agent Skill for Claude Code & any SKI. It is categorized as a Claude Skill with 213 GitHub stars.
design-harness is primarily written in Python. It covers topics such as agent-skills, ai-agents, claude-code.
You can find installation instructions and usage details in the design-harness GitHub repository at github.com/tigerless-labs/design-harness. The project has 213 stars and 33 forks, indicating an active community.
The top alternatives to design-harness on Agent Skills Hub include research-harness, econ-writing-skill, medsci-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: