BitterPillEngineering

Name: BitterPillEngineering
Availability: InStock
Author: starlink-awaken

Audit AI instruction sets for over-prompting using the Five Questions.

1|Updated Jun 10, 2026

Search Tags:#workflow #audit #claude #rules #prompt-engineering #token-savings #ai-instructions

Ready to run

npx skills add https://github.com/starlink-awaken/pai-universal --skill bitterpillengineering-starlink-awaken

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: BitterPillEngineering
Source: https://github.com/starlink-awaken/pai-universal/tree/main/templates/packs/BitterPillEngineering/src
Command: npx skills add https://github.com/starlink-awaken/pai-universal --skill bitterpillengineering-starlink-awaken

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Audits AI instruction sets for over-prompting using the Five Questions to classify each rule (CUT, RESOLVE, MERGE, EVALUATE, SHARPEN, MOVE, KEEP). It guides reductions in scaffolding to improve output quality and efficiency, and supports two workflows: Audit (full-system evaluation reading all force-loaded files from settings.json and producing token-savings estimates) and QuickCheck (single-file, fast keep/cut/sharpen verdict).

Core Features & Use Cases

Applies the Five Questions to every rule to determine necessity or redundancy.
Produces a categorized report with estimated line and token savings.
Supports two workflows (Audit and QuickCheck) for scalable and quick validations.
Keeps synchronization requirements (loadAtStartup and postCompactRestore.fullFiles) in sync.

Quick Start

Run the BitterPillEngineering skill to perform an Audit or QuickCheck workflow on your instruction set.

Frequently Asked Questions about BitterPillEngineering

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

FAQPage Schema

How do I audit AI prompts for over-prompting and reduce token usage?▼

An AI prompt audit evaluates instruction sets to classify rules as CUT, RESOLVE, MERGE, EVALUATE, SHARPEN, MOVE, or KEEP. This prunes redundant scaffolding to improve output quality and provides estimated token savings.

What is the best way to evaluate redundant rules in Claude AI instructions?▼

Evaluating redundant rules in Claude AI instructions uses the Five Questions framework to assess necessity. It categorizes each rule to determine if it should be kept, cut, or sharpened, producing a report with estimated line and token savings.

Can I run a quick check on a single AI instruction file instead of a full system audit?▼

Yes, you can run a QuickCheck workflow to perform a fast single-file audit. This provides a rapid keep, cut, or sharpen verdict for individual AI instruction files, compared to the full-system Audit workflow that reads all force-loaded files.

Why do my AI prompt rules need loadAtStartup and postCompactRestore.fullFiles synchronized?▼

Synchronizing loadAtStartup and postCompactRestore.fullFiles in settings.json ensures the audit framework stays in sync with your configuration. This alignment is required so the full-system evaluation accurately reads all force-loaded instruction files.

What are the limitations of using an automated prompt audit framework?▼

The prompt audit framework relies on settings.json synchronization and requires force-loaded files to be properly configured. If loadAtStartup and postCompactRestore.fullFiles are not aligned, the full-system evaluation cannot accurately read or audit the instruction set.