by lakeday-org · AI Tool · ★ 315
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
npm install -g @lakeday/perch
Taken 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 | 315 |
| Forks | 19 |
| Language | JavaScript |
| Category | AI Tool |
| License | MIT |
| Quality Score | 66/100 |
| Open Issues | 17 |
| Last Updated | 2026-09-29 |
| Created | 2026-09-16 |
| Platforms | cli, node |
| Est. Tokens | ~14k |
<img alt="perch"...
Looking for a perch alternative? If you're comparing perch with other ai tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Local codebase intelligence CLI + MCP server for AI coding agents: SQLite code graph, 28 languages, 287 comman
The missing linter and lsp for AI coding assistants. Validate CLAUDE.md, AGENTS.md, SKILL.md, hooks, MCP. Plug
The code quality toolkit for the agentic AI era. Find dead code, clones, and scaffolding across 15 languages.
AI writes code. This automates everything else · 24 plugins · 49 agents · 44 skills · for Claude Code, OpenCod
An AI-powered GitHub code review tool that uses LLMs to detect high-confidence, high-impact issues—such as sec
Official SonarQube MCP Server for code quality and security in AI agents
Explore other popular ai tool tools:
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: