skills.rest
tabooes
tabooesCOMMUNITY
Explore all skills by this author →
GitHub

context-engineering-advisor

Diagnose context stuffing and implement boundary-driven AI workflow improvements.

1|Updated Mar 30, 2026
Search Tags:#RAG#context-engineering#memory-architecture#retrieval-optimization#PM-workflow#context-stuffing#boundary-ownership
One-click install
npx skills add https://github.com/tabooes/pm_skills --skill context-engineering-advisor-tabooes
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: context-engineering-advisor
Source: https://github.com/tabooes/pm_skills/tree/main/skills/context-engineering-advisor
Command: npx skills add https://github.com/tabooes/pm_skills --skill context-engineering-advisor-tabooes

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Diagnose context stuffing vs. context engineering to improve AI workflow reliability and reduce token waste.

Core Features & Use Cases

  • Interactive diagnosis to identify context boundaries, ownership, and memory architecture.
  • STEP-based framework (Research → Plan → Reset → Implement) to prevent context rot.
  • Guidance for binding context to decisions and retrieval strategy.

Quick Start

Run the Context Engineering Advisor on your AI workflow to diagnose context stuffing and implement boundary-driven improvements.

Frequently Asked Questions about context-engineering-advisor

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

FAQPage Schema
What is the difference between context stuffing and context engineering in AI workflows?▼

Context stuffing overloads the AI prompt with irrelevant data, whereas context engineering structures memory boundaries and retrieval to improve consistency and reduce token waste in AI workflows.

How do I implement boundary ownership and episodic retrieval for AI memory architecture?▼

You implement boundary ownership and episodic retrieval by applying a two-layer memory design to separate context, binding specific retrieval strategies to decisions to prevent context rot.

How do I use the Research Plan Reset Implement cycle to prevent context rot?▼

You use the Research→Plan→Reset→Implement cycle as a step-based framework to diagnose context boundaries, reset token states between phases, and bind context directly to implementation decisions.

Does RAG retrieval optimization require a two-layer memory design to reduce token waste?▼

RAG retrieval optimization benefits from a two-layer memory design to establish context boundaries, ensuring episodic retrieval fetches only decision-relevant data and actively reduces token waste.

Why does my AI workflow suffer from context rot and inconsistent outputs during PM workflows?▼

AI workflows suffer from context rot during PM workflows when context stuffing lacks boundary ownership, causing the model to lose track of decisions without structured episodic retrieval.

Can I diagnose context stuffing in my existing AI workflow without changing the entire memory architecture?▼

You can diagnose context stuffing in existing AI workflows interactively to identify context boundaries, then apply targeted episodic retrieval and boundary ownership without rebuilding the entire memory architecture.

Related Skills

Explore More Product & Management Skills→
selcukyucelselcukyucel
1

cost-estimate

Estimate token usage and monthly costs for proposed AI automations.

Community
Advanced
roberttmadsen13-delroberttmadsen13-del

context-engineering-advisor

Diagnose context stuffing and guide teams toward bounded memory architectures.

Community
Advanced
devendrapratapsinghdevendrapratapsingh
1

memory-management

Design AI conversation memory systems with context window optimization and RAG.

Community
Advanced
metabenchmetabench

endurance

Manage long-running agent processes with external state files and auto-prompting workflows.

Community
Advanced