advance-minimax-m2-cursor-rules: Agentic-first Cursor Rules powered by MiniMax M2 — clarify-first prompting, interleaved thinking, and full

by madebyaris · MCP Server · ★ 113

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 70/100

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.

agentic-aiai-codingai-workflowcode-generationcursorcursor-idecursor-rulesdeveloper-toolsmcpminimax

Quick Facts

Stars113
Forks11
LanguageJavaScript
CategoryMCP Server
LicenseMIT
Quality Score70/100
Open Issues3
Last Updated2026-05-29
Created2025-12-08
Platformsmcp, node
Est. Tokens~24k

About advance-minimax-m2-cursor-rules

MiniMax M3 Cursor Rules A durable execution spine for repo-scale engineering on M3 + Cursor 3.7 — with frontier-agent coding judgment and reasoning protocols distilled into rules any model can run. Tuned for MiniMax M3 (1M-token MSA context, native multimodal input) and Cursor 3.7 (Agents

Compatible Skills

These tools work well together with advance-minimax-m2-cursor-rules for enhanced workflows:

  • Frame — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (51%)

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How this security grade is produced

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:

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