eiirp

Name: eiirp
Availability: InStock
Author: weiping

Organize session outputs into brain pages and skill graph structures.

1|Updated May 9, 2026

Search Tags:#knowledge management #gap analysis #post-work organization #schema-driven filing #citation and linking #skill graph audit #DRY MECE

Ready to run

npx skills add https://github.com/weiping/gbrain-cn --skill eiirp

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: eiirp
Source: https://github.com/weiping/gbrain-cn/tree/main/skills/eiirp
Command: npx skills add https://github.com/weiping/gbrain-cn --skill eiirp

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

EIIRP prevents knowledge from getting stuck in chat by auditing what you produced and filing it into the correct brain locations, while also turning repeatable work into maintainable skills.

Core Features & Use Cases

7-Phase Post-Work Audit: Inventories outputs, determines destinations from the active schema pack, validates schema coverage, files enriched pages, audits the skill graph for DRY+MECE, verifies resolvability, and reports results.
Knowledge-to-Brain Filing: Creates or updates pages for people, companies, deals, meetings, concepts, projects, civic, writing, guides, and analysis with citations, links, timelines, and entity backlinks.
Skill Graph Hardening: Identifies reusable capability patterns, checks for overlap and bypassed paths, proposes skillify actions, and enforces deterministic routing so nothing becomes ambiguous.
Idempotent, Schema-Pack Driven: Uses the active schema pack as the source of truth (with a confidence floor for schema suggestions) to avoid hard-coded directory logic.

Quick Start

Use EIIRP after a deep research thread to organize all outputs from that session into the correct brain pages and skill graph structure.

Frequently Asked Questions about eiirp

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

FAQPage Schema

How do I organize research outputs into a permanent knowledge base?▼

To organize research outputs into a permanent knowledge base, this skill audits your completed work session, inventories all outputs, and files them into correct schema-driven destinations. It converts reusable patterns into durable skills.

What is the best way to turn repeatable research patterns into maintainable skills?▼

The best way to turn repeatable patterns into maintainable skills is through a DRY and MECE skill graph audit that identifies reusable capabilities, proposes skillify actions, and enforces deterministic routing to prevent ambiguity.

How does schema-driven filing route post-work session outputs?▼

Schema-driven filing routes post-work session outputs by using the active schema pack as the source of truth to determine destinations, validate coverage, and avoid hard-coded directory logic for enriched page writes.

Can I use this to file multi-source analysis outputs with entity backlinks?▼

Yes, you can file multi-source analysis outputs with entity backlinks. The process creates or updates enriched pages for concepts and projects with citations, links, timelines, and backlinks to ensure resolvability.

What are the limitations of using a schema pack for knowledge management?▼

A limitation of schema-driven knowledge management is its reliance on the active schema pack, which requires a confidence floor for schema suggestions and necessitates a 7-phase lifecycle audit to verify resolvability and avoid gaps.