analyze-context

Manage iterative multi-file analysis workflows with persistent memory files.

2|2|Updated Mar 2, 2026

Search Tags:#workflow #context #analysis #auditing #memory #iterative

Ready to run

npx skills add https://github.com/medhatgalal/Core-Prompts --skill analyze-context

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: analyze-context
Source: https://github.com/medhatgalal/Core-Prompts/tree/main/.gemini/skills/analyze-context
Command: npx skills add https://github.com/medhatgalal/Core-Prompts --skill analyze-context

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill streamlines complex, multi-file analysis tasks by providing a structured workflow that maintains context and accumulates insights across iterative processing steps, preventing data loss and ensuring comprehensive analysis.

Core Features & Use Cases

Iterative Processing: Handles tasks requiring sequential analysis of multiple items (files, transcripts, etc.).
Context Maintenance: Uses dedicated memory files (<task>-context.md, <task>-todo.md, <task>-insights.md) to preserve state across sessions and memory compactions.
Workflow Guidance: Enforces rules for creating, updating, and consolidating memory files to prevent sprawl and ensure a single source of truth.
Use Case: Auditing a large codebase for specific patterns or drift across numerous .md files, ensuring all findings are captured and synthesized.

Quick Start

Use analyze-context to audit all ssot/*.md files for drift.

Frequently Asked Questions about analyze-context

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

FAQPage Schema

How do I maintain context when analyzing multiple files across different sessions?▼

Iterative analysis maintains context across sessions by using dedicated memory files like `<task>-context.md` and `<task>-insights.md` to preserve state and prevent data loss during multi-file processing.

What is the best way to audit a large codebase for documentation drift?▼

Auditing a large codebase for drift is best handled by an iterative analysis workflow that sequentially processes items, accumulates findings in memory files, and synthesizes all discoveries to ensure comprehensive coverage.

Can I use this iterative analysis workflow for processing multiple transcripts?▼

Yes, this workflow handles sequential analysis of multiple items, allowing you to process transcripts iteratively while accumulating insights and preserving state across memory compactions.

Does multi-file context accumulation work without losing previous insights?▼

Context accumulation prevents data loss by enforcing canonical memory file structures and workflow rules, ensuring all gathered insights are captured, updated, and consolidated into a single source of truth.

How do I prevent memory file sprawl during project-wide analysis initiatives?▼

Preventing memory file sprawl requires enforcing strict workflow rules for creating, updating, and consolidating memory files, which ensures a single source of truth throughout the analysis process.