Advance Minimax M3 Cursor Rules

Free

Agentic-first Cursor Rules powered by MiniMax M3 - clarify-first prompting, interleaved thinking, and full tool orchestration for production-ready AI coding

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Type

Open Source

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About Advance Minimax M3 Cursor Rules

A durable execution spine for repo-scale engineering on MiniMax 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 Window, canvases, Design Mode, /worktree, /best-of-n, Await, MCP Apps). Written to stay useful across model changes. Features lean always-on core rules for reasoning protocol, solver loop, scope control, code discipline, and M3 long-context/multimodal input discipline. Includes fable5-* craft rules for locate-before-write, root-cause method, simplicity taste, test integrity, hypothesis ledgers, and stuck-strategy ladder. Progressive depth allows 18 requestable rules + 7 skill packs to load only when needed. Provides evidence-backed closeouts with explicit status labels (verified/unverified/blocked/multimodal-grounded), minimum-proof rules per change type, and red→green proof for bug fixes. Portable docs/AGENTS.md carries the same behavior to non-Cursor IDEs and CLIs.

Key Features

Agentic-first Cursor Rules with clarify-first prompting and interleaved thinking

Full tool orchestration for production-ready AI coding

Lean always-on core: two durable rules carry reasoning protocol, solver loop, scope control, code discipline, M3 long-context discipline, M3 multimodal input discipline, and strict proof contract

Frontier craft distilled: fable5-* craft rules transfer SWE-Bench-class agent judgment (locate-before-write, root-cause method, simplicity taste, test integrity, hypothesis ledgers, stuck-strategy ladder)

Progressive depth: 18 requestable rules + 7 skill packs load only when needed, keeping context clean

M3 long-context discipline: 1M-token MSA context retention and compression cadence

M3 multimodal-native: image and video input grounding with design-parity and screenshot-triage workflow

Cursor 3.7 surface guidance: Agents Window, canvases, Design Mode, /worktree, /best-of-n, Await, MCP Apps

Honest tool use: agent works current runtime, no invented tools or stale wrappers

Evidence-backed closeouts: explicit status labels (verified/unverified/blocked/multimodal-grounded), minimum-proof rules per change type, red→green proof for bug fixes

Pros & Cons

Pros

Agentic-first approach with clarify-first prompting reduces ambiguity
Durable execution spine works across model changes, not tied to a single model version
Honest tool use prevents hallucinated or stale tool wrappers
Evidence-backed closeouts with explicit pass/fail labels improve reliability
Progressive depth avoids context bloat by loading rules only when needed
Supports multimodal inputs (images and videos) for visual reasoning
Explicit guidance for Cursor 3.7 features like canvases, Design Mode, and MCP Apps
Portable to non-Cursor IDEs and CLIs via AGENTS.md, extending usability

Cons

Primarily designed for Cursor IDE, may not fully benefit other editors without porting documentation
Tuned for MiniMax M3; other models may not leverage all optimizations effectively
Learning curve for users unfamiliar with Cursor rules and the concept of progressive depth
Requires manual installation and setup via cloning the repository
Some features (like long-context discipline) depend on M3's 1M-token context, not available on all models

Best For

Repo-scale engineering on MiniMax M3 + Cursor 3.7Production-ready AI coding with frontier-agent judgmentBuilding and debugging software with AI assistants in CursorHandling large codebase context (up to 1M tokens) with efficient compressionMultimodal AI coding: using image and video inputs to ground visual claimsStructured AI agent workflows with minimum-proof verification and status tracking