by TheRealSeanDonahoe · MCP Server · ★ 156
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
npm install -g @ijfw/install && ijfw-installTaken from the project's README on GitHub. Check the security audit before running it.
Flagged: reads agent memory. 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 | 156 |
| Forks | 26 |
| Language | JavaScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 60/100 |
| Open Issues | 2 |
| Last Updated | 2026-05-01 |
| Created | 2026-04-16 |
| Platforms | claude-code, cli, codex, gemini, mcp, node |
| Est. Tokens | ~146k |
Your AI tools are brilliant, forgetful, undisciplined, and alone. One install fixes all four. IJFW is one shared brain, and a full operating layer, for every AI coding tool you use. Install it once and your tools remember across sessions, plan before they build, check each other's work for hallucinations, pull in the right specialist for the job, and quietly cut your token bill.
These tools work well together with ijfw for enhanced workflows:
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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: