project-cognition

Organize project knowledge into principles, domain mappings, and runbooks.

Updated Aug 31, 2024
One-click install
npx skills add https://github.com/iheCoder/Lib --skill project-cognition
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: project-cognition
Source: https://github.com/iheCoder/Lib/tree/main/skill/project-cognition
Command: npx skills add https://github.com/iheCoder/Lib --skill project-cognition

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a structured approach to capturing and organizing project-level knowledge across rules, domain relationships, and operational experience, preventing knowledge loss and accelerating onboarding.

Core Features & Use Cases

  • Core Manifest: store project principles, constraints, and validation requirements to guide changes.
  • Domain Knowledge: document system relationships, data flows, and key field definitions.
  • Runbooks: collect practical command sequences, troubleshooting steps, and checklists for operations.
  • Use Case: Onboarding new engineers or documenting architecture, read INDEX.md to determine where to place new cognitions and ensure incremental updates.

Quick Start

Open the Project Cognition tool and add a new cognition entry following the Update Protocol.

Frequently Asked Questions about project-cognition

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

FAQPage Schema
How do I organize project knowledge to prevent knowledge loss during engineering onboarding?

Organize project knowledge using a three-layer model that captures project principles, maps domain knowledge, and codifies runbooks. This structured approach prevents knowledge loss and accelerates onboarding by storing rules, system relationships, and operational experience.

What is the best way to document troubleshooting steps and operational maintenance checklists?

Document troubleshooting steps and maintenance checklists by creating runbooks within a project cognition structure. Runbooks collect practical command sequences and operational procedures, ensuring troubleshooting experience is codified and easily accessible for future maintenance.

How do I map domain knowledge and system data flows for software architecture documentation?

Map domain knowledge by documenting system relationships, data flows, and key field definitions within a structured cognition model. This captures critical architecture context, ensuring system relationships are explicitly recorded for engineering reference and onboarding.

Does this project knowledge management approach support incremental updates and versioned documentation?

Yes, project knowledge management supports versioned updates through a frontmatter-driven structure and incremental writing rules. Users read an index file to determine where to place new cognitions, ensuring documentation evolves safely without overwriting existing context.

Can I use this to capture project constraints and validation requirements for guiding code changes?

Yes, you can capture project constraints and validation requirements using a core manifest. This stores project principles and validation rules to guide changes, ensuring engineering teams respect existing constraints when modifying the codebase.

When should I use a three-layer model for indexing documentation instead of standard wiki pages?

Use a three-layer model for indexing documentation when you need to separate project principles, domain relationships, and operational runbooks. This structured approach prevents knowledge loss better than flat wiki pages by ensuring incremental, versioned updates across distinct cognition layers.