extractor

Extract professional knowledge from archived emails into markdown entries.

3|4|Updated Mar 11, 2026
One-click install
npx skills add https://github.com/nicsuzor/academicOps --skill extractor
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: extractor
Source: https://github.com/nicsuzor/academicOps/tree/main/archived/skills/extractor
Command: npx skills add https://github.com/nicsuzor/academicOps --skill extractor

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the process of identifying and extracting valuable professional knowledge from archived emails, converting them into structured markdown entries for a knowledge base.

Core Features & Use Cases

  • Intelligent Filtering: Assesses emails for importance based on predefined criteria (e.g., collaborations, milestones, financial records).
  • Structured Extraction: Converts important email content into well-formatted markdown files for people, projects, and events.
  • Use Case: Automatically process your inbox, identifying and saving key collaboration proposals, grant application outcomes, and significant professional contacts, ensuring no critical information is lost.

Quick Start

Run the /archive command to process the next email file.

Frequently Asked Questions about extractor

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

FAQPage Schema
How do I extract important knowledge from archived emails?

To extract knowledge from archived emails, this Skill automates the identification of professional information and converts important email content into structured markdown knowledge base entries.

What's the best way to convert professional email archives into markdown?

Converting email archives into markdown is handled by assessing documents for information worth preserving, such as projects and financial records, and formatting them into structured markdown files.

How does automated email archiving classify important professional information?

Automated email archiving classifies professional information by utilizing LLM judgment to assess predefined criteria like collaborations, milestones, publications, and important contacts.

Can I use this to process emails for specific projects and contacts?

Processing emails for specific projects and contacts is supported by filtering for important professional activities, collaborations, and significant contact details to ensure no critical information is lost.

How do I start processing my inbox to save key collaboration proposals?

To start processing your inbox and saving collaboration proposals, run the /archive command to process the next email file for intelligent extraction.

Do I need a separate storage skill to save extracted email knowledge?

A separate storage skill is needed because this Skill delegates the actual storage of the extracted and classified knowledge base entries to a 'remember' skill.