grade-rule — for Claude Code grade-rule, boilerplate-vite-supabase-mui-cursor, community, for Claude Code, ide skills, EXECUTE, ATTACHED, CONTEXT, INSTEAD, rubric

v1.0.0
GitHub

About this Skill

Ideal for AI agents that need do not execute the other attached rule context. instead, grade it:. grade-rule is an AI agent skill for do not execute the other attached rule context. instead, grade it:.

Features

DO NOT EXECUTE THE OTHER ATTACHED RULE CONTEXT. INSTEAD, GRADE IT:
Cursor Command Quality Rubric
Here's a rubric for grading Cursor commands on a 1-5 scale across key dimensions:
Clarity of Instructions (Weight: 25%)
------- -------------

# Core Topics

for Claude Code EXECUTE ATTACHED CONTEXT INSTEAD rubric
TMI-apps TMI-apps
[2]
[0]
Updated: 4/19/2026

Skill Overview

Start with fit, limitations, and setup before diving into the repository.

Ideal for AI agents that need do not execute the other attached rule context. instead, grade it:. grade-rule is an AI agent skill for do not execute the other attached rule context. instead, grade it:.

Core Value

grade-rule helps agents do not execute the other attached rule context. instead, grade it:. Boilerplate for the stack boilerplate-vite-supabase-mui-cursor with no opinionated app hosting.

Ideal Agent Persona

Ideal for AI agents that need do not execute the other attached rule context. instead, grade it:.

↓ Capabilities Granted for grade-rule

Applying DO NOT EXECUTE THE OTHER ATTACHED RULE CONTEXT. INSTEAD, GRADE IT:
Applying Cursor Command Quality Rubric
Applying Here's a rubric for grading Cursor commands on a 1-5 scale across key dimensions:

! Prerequisites & Limits

  • DO NOT EXECUTE THE OTHER ATTACHED RULE CONTEXT. INSTEAD, GRADE IT:
  • 3 Mostly clear but some vague sections require the assistant to make assumptions.
  • 2 Frequently unclear. Assistant must guess intent in multiple places.

About The Source

The section below comes from the upstream repository. Use it as supporting material alongside the fit, use-case, and installation summary on this page.

Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is grade-rule?

Ideal for AI agents that need do not execute the other attached rule context. instead, grade it:. grade-rule is an AI agent skill for do not execute the other attached rule context. instead, grade it:.

How do I install grade-rule?

Run the command: npx killer-skills add TMI-apps/boilerplate-vite-supabase-mui-cursor/grade-rule. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for grade-rule?

Key use cases include: Applying DO NOT EXECUTE THE OTHER ATTACHED RULE CONTEXT. INSTEAD, GRADE IT:, Applying Cursor Command Quality Rubric, Applying Here's a rubric for grading Cursor commands on a 1-5 scale across key dimensions:.

Which IDEs are compatible with grade-rule?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for grade-rule?

DO NOT EXECUTE THE OTHER ATTACHED RULE CONTEXT. INSTEAD, GRADE IT:. 3 Mostly clear but some vague sections require the assistant to make assumptions.. 2 Frequently unclear. Assistant must guess intent in multiple places..

↓ How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add TMI-apps/boilerplate-vite-supabase-mui-cursor/grade-rule. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use grade-rule immediately in the current project.

Upstream Repository Material

The section below comes from the upstream repository. Use it as supporting material alongside the fit, use-case, and installation summary on this page.

Upstream Source

grade-rule

Install grade-rule, an AI agent skill for AI agent workflows and automation. Explore features, use cases, limitations, and setup guidance.

SKILL.md
Readonly
Upstream Repository Material
The section below comes from the upstream repository. Use it as supporting material alongside the fit, use-case, and installation summary on this page.
Upstream Source

grade-rule

DO NOT EXECUTE THE OTHER ATTACHED RULE CONTEXT. INSTEAD, GRADE IT:

Use the rubric below to evaluate the attached rule/command file. Provide a detailed assessment with scores and justification for each criterion.

Cursor Command Quality Rubric

Here's a rubric for grading Cursor commands on a 1-5 scale across key dimensions:

1. Clarity of Instructions (Weight: 25%)

ScoreDescription
5Crystal clear, unambiguous instructions. Each step is explicit with no room for misinterpretation. Uses precise language and concrete examples.
4Clear instructions with minor ambiguities. Assistant can reliably follow with minimal interpretation.
3Mostly clear but some vague sections require the assistant to make assumptions.
2Frequently unclear. Assistant must guess intent in multiple places.
1Confusing or contradictory instructions. High likelihood of misinterpretation.

Key questions:

  • Can the assistant execute this without asking clarifying questions?
  • Are technical terms defined or used consistently?
  • Are conditionals (if/then) explicitly stated?

2. Handling Ambiguous User Input (Weight: 25%)

ScoreDescription
5Explicitly defines how to handle vague/incomplete user requests. Includes fallback behaviors, clarification prompts, and decision trees for common ambiguities.
4Addresses most ambiguity scenarios with clear guidance. Minor edge cases may be unhandled.
3Some guidance for ambiguity, but relies on assistant judgment for many scenarios.
2Limited guidance. Assistant is left to improvise when user input is unclear.
1No consideration for ambiguous input. Command assumes perfect user requests.

Key questions:

  • Does it tell the assistant what to do when the user's request is incomplete?
  • Are there explicit "ask the user" triggers defined?
  • Does it prevent the assistant from making dangerous assumptions?

3. Structure & Organization (Weight: 15%)

ScoreDescription
5Logical flow with clear sections, headers, and hierarchy. Easy to scan and reference. Uses formatting (lists, code blocks) effectively.
4Well-organized with minor structural improvements possible.
3Adequate structure but could be clearer. Some sections feel out of place.
2Poorly organized. Important information buried or scattered.
1No discernible structure. Stream of consciousness.

4. Completeness (Weight: 15%)

ScoreDescription
5Covers all necessary scenarios including success paths, error handling, edge cases, and exit conditions. Nothing left implicit.
4Covers main scenarios well. Minor gaps in edge case handling.
3Handles happy path but misses several important scenarios.
2Significant gaps. Many scenarios require assistant to improvise.
1Incomplete. Missing critical steps or scenarios.

5. Actionability (Weight: 10%)

ScoreDescription
5Every instruction is directly actionable. Verbs are specific (e.g., "search for X in Y" vs "look around"). Outputs are clearly defined.
4Mostly actionable with occasional vague directives.
3Mix of actionable and abstract instructions.
2Many instructions are too abstract to execute directly.
1Instructions are philosophical rather than actionable.

6. Guardrails & Safety (Weight: 10%)

ScoreDescription
5Explicit boundaries on what the assistant should NOT do. Includes validation steps, confirmation prompts for destructive actions, and scope limits.
4Good guardrails for major risks. Minor oversights.
3Some guardrails but gaps in protection against common mistakes.
2Few guardrails. Assistant could easily go off-track.
1No guardrails. High risk of unintended consequences.

Scoring Template

Use this template to calculate the final grade:

Command: ____________________

| Criterion                    | Score (1-5) | Weight | Weighted |
|------------------------------|-------------|--------|----------|
| Clarity of Instructions      |             | 0.25   |          |
| Handling Ambiguous Input     |             | 0.25   |          |
| Structure & Organization     |             | 0.15   |          |
| Completeness                 |             | 0.15   |          |
| Actionability                |             | 0.10   |          |
| Guardrails & Safety          |             | 0.10   |          |
|------------------------------|-------------|--------|----------|
| TOTAL                        |             | 1.00   |    /5    |

Grade Scale:

  • A (4.5-5.0): Excellent - Ready to use with minimal improvements
  • B (3.5-4.4): Good - Solid foundation with some areas for enhancement
  • C (2.5-3.4): Adequate - Works but needs significant improvements
  • D (1.5-2.4): Poor - Major issues that need addressing
  • F (<1.5): Failing - Needs complete revision

Output Format

For each criterion:

  1. Score: Provide the score (1-5)
  2. Justification: Explain why this score was given, citing specific examples from the rule/command
  3. Suggestions: If score < 5, provide concrete suggestions for improvement

After scoring all criteria:

  1. Calculate the weighted total
  2. Assign the letter grade
  3. Provide an overall summary with prioritized recommendations

Related Skills

Looking for an alternative to grade-rule or another community skill for your workflow? Explore these related open-source skills.

View All

openclaw-release-maintainer

Logo of openclaw
openclaw

openclaw-release-maintainer is an AI agent skill for openclaw release maintainer.

★ 333.8k
⑂ 0
AI

widget-generator

Logo of f
f

Generate customizable widget plugins for the prompts.chat feed system

★ 149.6k
⑂ 0
AI

flags

Logo of vercel
vercel

flags is an AI agent skill for use this skill when adding or changing framework feature flags in next.js internals.

★ 138.4k
⑂ 0
Browser

pr-review

Logo of pytorch
pytorch

pr-review is an AI agent skill for pytorch pr review skill.

★ 98.6k
⑂ 0
Developer