pharaoh-context-gather

Retrieve rationale memories with IDs, text, and relevance scores from a Papyrus workspace.

24|Updated Feb 12, 2026
One-click install
npx skills add https://github.com/useblocks/pharaoh --skill pharaoh-context-gather
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: pharaoh-context-gather
Source: https://github.com/useblocks/pharaoh/tree/main/skills/pharaoh-context-gather
Command: npx skills add https://github.com/useblocks/pharaoh --skill pharaoh-context-gather

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Retrieve rationale memories from a Papyrus workspace to inform drafting decisions.

Core Features & Use Cases

  • Retrieve structured memories (memory_id, text, relevance_score) to feed downstream drafting, review, or planning tasks.
  • Ensure memories are relevant to the current feature/context and used to constrain design decisions.
  • Use Case: Before drafting or reviewing, pull memories to respect past constraints and conventions.

Quick Start

Invoke pharaoh-context-gather before drafting to fetch memory snippets from your Papyrus workspace.

Frequently Asked Questions about pharaoh-context-gather

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

FAQPage Schema
How do I retrieve rationale memories from a Papyrus workspace to inform drafting decisions?

You can retrieve rationale memories from a Papyrus workspace by invoking pharaoh-context-gather before any drafting or review task. It returns a structured JSON array of memories with IDs, text, and relevance scores to guide your drafting decisions.

What are design rationale memories used for in the drafting process?

Design rationale memories are used to feed downstream drafting, review, or planning tasks. Retrieving these memories ensures your drafts respect past preconditions, design-decisions, and established conventions within the project.

Do I need a .papyrus directory to fetch context memories?

Yes, you need a .papyrus directory in your project to fetch context memories. The retrieval process checks for this directory and gracefully returns an empty JSON list if no workspace or matching memories exist.

How do I get structured context with relevance scores before reviewing a draft?

To get structured context with relevance scores before reviewing a draft, use a memory-retrieval process that queries your Papyrus workspace. It outputs a JSON array containing memory_id, text, and relevance_score for each matched snippet.

What happens if there are no matching rationale memories in the Papyrus workspace?

If there are no matching rationale memories in the Papyrus workspace, the retrieval process gracefully returns an empty list. This allows downstream drafting and review tasks to proceed without interruption.