cheat-bump

Automate rubric and bucket boundary upgrades with auditable governance.

12|Updated May 29, 2026
One-click install
npx skills add https://github.com/Jason5330/ai-self-eval --skill cheat-bump
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: cheat-bump
Source: https://github.com/Jason5330/ai-self-eval/tree/main/skills/cheat-bump
Command: npx skills add https://github.com/Jason5330/ai-self-eval --skill cheat-bump

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the process of upgrading calibration rubrics and bucket boundaries, enabling controlled, auditable changes to scoring systems and reducing drift in model evaluation.

Core Features & Use Cases

  • Complete rubric bump mode: performs a full, cross-model evaluated rubric upgrade with enforced steps and review.
  • Bucket-only mode: recalibrates only bucket boundaries for lightweight adjustment without altering the rubric formula.
  • Phase-driven workflow: includes proposed formulas, validation protocols, blind scoring sub-agents, and state tracking for auditability.

Quick Start

Trigger a rubric bump by issuing /cheat-bump --propose "<new formula>" or run /cheat-bump --bucket-only to perform a lightweight bucket recalibration.

Frequently Asked Questions about cheat-bump

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate calibration rubric upgrades for AI scoring systems?

You can automate calibration rubric upgrades by triggering a formal proposal mode that enforces cross-model audits, blind sub-agent scoring workflows, and updates state tracking files to ensure auditable governance over the new formulas.

What is bucket-only recalibration for LLM quality assurance?

Bucket-only recalibration is a lightweight adjustment process that modifies bucket boundaries without altering the core rubric formula, providing a quick method to correct scoring drift in evaluation pools.

How does cross-model audit work during rubric calibration?

Cross-model auditing works by running blind sub-agent scoring workflows across different models to validate proposed rubric formulas, ensuring the upgraded boundaries maintain evaluation consistency and reduce drift.

When do I need formal input to bump calibration rubrics?

You need formal input when executing a complete rubric bump, which requires submitting a proposed formula to trigger enforced validation protocols, cross-model reviews, and state updates for full auditability.

What files are updated during an automated rubric bump process?

The automated rubric bump process updates rubric_notes.md, rubric-memo.md, and .cheat-state.json to track state changes, document validation protocols, and maintain auditable governance records for the scoring system.

Can I adjust bucket boundaries without changing the rubric formula?

Yes, you can adjust bucket boundaries independently by running a bucket-only mode, which performs lightweight recalibration on the evaluation pools while leaving the underlying rubric formula completely intact.