edi-self-improve

Extract tacit editorial decisions into reusable rules for knowledge files.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/Telepotch/hirano-edi-on-claude-code --skill edi-self-improve
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: edi-self-improve
Source: https://github.com/Telepotch/hirano-edi-on-claude-code/tree/main/.claude/skills/edi-self-improve
Command: npx skills add https://github.com/Telepotch/hirano-edi-on-claude-code --skill edi-self-improve

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Efficiently capture the hidden reasoning behind editorial decisions from a session and translate it into explicit, reusable knowledge that can guide future work.

Core Features & Use Cases

  • Extract tacit decisions and rationale from editing sessions.
  • Route new rules to EDITORIAL.md, LEXICON.jsonl, STYLE.md, and blueprint as appropriate.
  • Preserve reasoning for future auditing and onboarding.

Quick Start

Provide a current session for analysis and ask the AI to extract tacit knowledge, convert it into actionable rules, and route items to the appropriate knowledge layer.

Frequently Asked Questions about edi-self-improve

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

FAQPage Schema
How do I extract tacit knowledge from an editing session?

You can extract tacit knowledge from an editing session by analyzing implicit editorial decisions and converting them into explicit, reusable rules. This process identifies why decisions were made and validates them for stability across future sessions.

What is the best way to turn implicit editorial decisions into reusable rules?

Turning implicit editorial decisions into reusable rules requires capturing the hidden reasoning behind them during a session. New rules are written in imperative form and validated for applicability across future work.

How do I route new editorial rules to knowledge layers like EDITORIAL.md or STYLE.md?

Routing new editorial rules to knowledge layers like EDITORIAL.md or STYLE.md involves assigning extracted candidates to the appropriate file based on their function. This prevents duplicating documented rules and ensures proper memory routing.

Can I analyze a current session to identify why editorial decisions were made?

Yes, you can analyze a current session to identify why editorial decisions were made. By providing the session for analysis, the system extracts tacit knowledge and applies it across the current project to preserve reasoning for future auditing.

How do I avoid duplicating documented rules when extracting session knowledge?

To avoid duplicating documented rules when extracting session knowledge, the process checks existing entries across EDITORIAL.md, LEXICON.jsonl, STYLE.md, and blueprints. It ensures new imperative rules are distinct and reflected in memory.