Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/madebyaris/advance-minimax-m3-cursor-rulesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/rules/madebyaris/advance-minimax-m3-cursor-rules/skill-authoring)<a href="https://agentmods.dev/rules/madebyaris/advance-minimax-m3-cursor-rules/skill-authoring"><img src="https://agentmods.dev/badge/rules/madebyaris/advance-minimax-m3-cursor-rules/skill-authoring/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/rules/madebyaris/advance-minimax-m3-cursor-rules/skill-authoring"><img src="https://agentmods.dev/badge/rules/madebyaris/advance-minimax-m3-cursor-rules/skill-authoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00042 | $0.00748 |
| Opus 5 | $0.00021 | $0.00374 |
| Sonnet 5 | $0.00008 | $0.00150 |
| Haiku 4.5 | $0.00004 | $0.00075 |
Grade A, and why
skill-authoring scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Authoring
Use this rule when creating, revising, or evaluating .cursor/skills/* content.
Rule vs Skill
- Put durable, universal behavior in always-on rules.
- Use a skill for repeatable workflows, domain-specific heuristics, or tasks that need examples and reference material.
- If the content only matters for one file type or one domain, prefer a skill or requestable rule over expanding the core.
Skill Shape
Each skill should clearly provide:
- what it is for
- when to use it
- what to inspect first
- the workflow or decision sequence
- any output or verification expectations
Frontmatter Contract
Use YAML frontmatter on every SKILL.md.
Minimum:
---
name: my-skill
description: >
What this skill does and the user-language triggers for when to use it.
license: MIT
metadata:
version: "1.0.0"
category: workflow
sources:
- Official docs or standards
model_assumptions: [] # optional; see below
---
Rules:
namemust match the directory name exactly.descriptionmust include concrete trigger language, not vague capability claims.licenseshould be explicit so skills stay portable outside this repo.metadata.versionshould change when the skill meaningfully evolves.metadata.categoryshould describe the domain or workflow.metadata.sourcesshould name current authoritative sources when the skill depends on external behavior.metadata.model_assumptions(optional) should name the model capabilities the skill depends on, e.g.:multimodal-input: required— the skill expects the user can attach images/video that the model can read nativelylong-context: recommended— the skill expects a 1M-class context window for the loader to be usefulcursor-3-runtime: required— the skill expects the Cursor 3.7 / Agents Window surface
Progressive Disclosure
- Keep
SKILL.mdfocused on the main workflow. - Move large examples, extended references, and category catalogs into companion files such as
reference.md. - Load deeper material only when the task actually needs it.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 85 lines · 42 tokens per session scan A 5e0d7152d2bc
skill-authoring is a cursor rule published in the GitHub repository madebyaris/advance-minimax-m3-cursor-rules (125 stars, last pushed 2mo ago), licensed MIT. It adds 42 tokens to every session and 748 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other cursor rules, from other repositories
git-commit
Use this when the user asks for a git commit, commit message, or commit command.
learnship
Activate learnship agentic engineering workflows — structured phases, persistent memory, learning partner, and impeccable UI design. Use whenever a user is working on a software project or asks about project planning, phases, workflows, or how to build something.
behavior-principles
Global behavioral principles for all AI-assisted work in this repository. Covers thinking before coding, simplicity, surgical changes, goal-driven execution, and communication standards.
coding
Core coding behavior for this repository. Always prefer cautious, minimal, reversible changes.
testing
Optional Spring Boot example-pack testing rules. Apply only when editing an adopted project or spring-boot profile output.
workflow
Workflow canonical adapter and intent routing rules.