No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by zgsm-ai · Agent Tool · ★ 4.4k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is costrict safe to install? View the security audit →
CoStrict Strict AI Coder for Enterprises Free • Open Source • Private Deployment 简体中文 | English CoStrict is a free, open-source AI-powered coding assistant designed for enterprise-grade development. With support for private deployment, it's the optimal choice for organizations requiring secure, standardized AI development workflows. ✨ Core Capabilities Standardized AI c
| Stars | 4,430 |
| Forks | 202 |
| Language | TypeScript |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 54.8816383058042/100 |
| Open Issues | 10 |
| Last Updated | 2026-09-17 |
| Created | 2025-04-10 |
| Platforms | claude-code, cli, gemini, node |
| Est. Tokens | ~28547k |
These tools work well together with costrict for enhanced workflows:
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costrict is Costrict - strict AI coder for enterprises, quality first, including AI Agent, AI CodeReview, AI Completion.. It is categorized as a Agent Tool with 4.4k GitHub stars.
costrict is primarily written in TypeScript. It covers topics such as agent, agentic-ai, ai.
You can find installation instructions and usage details in the costrict GitHub repository at github.com/zgsm-ai/costrict. The project has 4.4k stars and 202 forks, indicating an active community.
costrict is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to costrict on Agent Skills Hub include cc-skills-golang, openpencil, agentsys. 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: