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comment-implementer

Classify client emails and implement document edits in legal workflows.

Updated Jan 13, 2026
Search Tags:#automation#checklist#email#classify#legal-research#document-edits
One-click install
npx skills add https://github.com/aech-ai/aech-cli-legal --skill comment-implementer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: comment-implementer
Source: https://github.com/aech-ai/aech-cli-legal/tree/main/aech_cli_legal/skills/comment-implementer
Command: npx skills add https://github.com/aech-ai/aech-cli-legal --skill comment-implementer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires aech-cli-msgraph, aech-cli-legal, aech-cli-inbox-assistant.

What problem does it solve?

This Skill automates triaging client communications, implementing document changes, and tracking progress to reduce manual back-and-forth and ensure timely approvals.

Core Features & Use Cases

  • Automated Classification: Classify incoming client emails as edit requests, research questions, or informational notes.
  • Document Edits & Redlines: Apply approved edits to draft documents and generate redlines for review.
  • Research & Tracking: Perform focused legal research and produce memos, then update project checklists.
  • Workflow Orchestration: Integrates with inbox and collaboration tools to keep stakeholders informed and tasks tracked.

Quick Start

Run python scripts/classify_email.py --message-id 'ABC123' to classify an incoming email, then run python scripts/implement_edits.py to apply approved changes to the draft, followed by python scripts/update_checklist.py --add 'Edits approved by client' to update the project checklist.

Frequently Asked Questions about comment-implementer

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

FAQPage Schema
How do I automate triaging client emails for legal document edits?▼

You can automate client email triage by classifying incoming messages as edit requests, research questions, or status updates, then coordinating document edits and checklist updates using Python scripts.

Can I generate redlines automatically from client edit requests in emails?▼

Yes, client edit requests can be processed to apply approved changes to draft documents and generate redlines for review using the implement_edits script within a Python environment.

Does this legal workflow automation require Microsoft Graph or inbox assistant CLI tools?▼

Yes, the workflow integrates with external CLIs including aech-cli-msgraph, aech-cli-legal, and aech-cli-inbox-assistant to perform email classification, legal research, and document editing actions.

What is the best way to track legal research tasks and client approvals?▼

The best way to track research tasks is by updating project checklists automatically after performing focused legal research, ensuring stakeholders stay informed and task progress is recorded.

Do I need a Python environment to run document edit and email classification scripts?▼

Yes, a Python environment is required to run the scripts in the scripts/ directory for classifying emails, implementing document edits, and updating legal project checklists.

When should I not use automated email classification for legal document workflows?▼

Automated email classification is not suitable for unstructured client communications lacking clear edit requests, research questions, or status updates that the triage system is designed to parse.

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