ingest-system-prompt

Parse external AI system prompts into structured memory entries via the MemoryStore API.

2|Updated Apr 8, 2026
One-click install
npx skills add https://github.com/DojoGenesis/gateway --skill ingest-system-prompt
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ingest-system-prompt
Source: https://github.com/DojoGenesis/gateway/tree/main/plugins/wisdom-garden/skills/ingest-system-prompt
Command: npx skills add https://github.com/DojoGenesis/gateway --skill ingest-system-prompt

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The skill ingests external AI system prompts—such as those from Cursor, GitHub Copilot, or custom agents—and stores them as structured MemoryEntries with explicit behavioral indicators, enabling auditing, versioning, and cross‑referencing of agent behavior.

Core Features & Use Cases

  • Canonical Section Parsing: Breaks prompts into core instructions, behavioral rules, tool definitions, constraints, and safety rules.
  • ADA Disposition Extraction: Detects pacing, depth, tone, initiative, and trust indicators and records them as MemorySeeds.
  • Memory Storage: Saves the full prompt and parsed metadata in the Dojo MemoryStore, linking entries and seeds for later retrieval.
  • Use Cases: Auditing third‑party AI behavior, migrating prompts between tools, comparing multiple system prompts, and maintaining version‑controlled prompt repositories.

Quick Start

Use the ingest-system-prompt skill to store the system prompt file my_prompt.md into Dojo memory.

Frequently Asked Questions about ingest-system-prompt

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

FAQPage Schema
How do I convert AI system prompts into structured memory for auditing?

You convert AI system prompts into structured memory by parsing them into canonical sections like core instructions, behavioral rules, and constraints, then storing them as MemoryEntry objects with linked MemorySeeds.

What are ADA disposition indicators when extracting behavior from system prompts?

ADA disposition indicators are behavioral metadata extracted from system prompts that detect pacing, depth, tone, initiative, and trust levels, which are then recorded as MemorySeeds for cross-referencing agent behavior.

Can I use this to migrate and version control system prompts between different AI tools?

You can migrate and version control system prompts by ingesting external prompts into a centralized MemoryStore, saving the full prompt text and parsed metadata for later retrieval, comparison, and version tracking.

How do I store GitHub Copilot or Cursor system prompts for behavioral analysis?

You store GitHub Copilot or Cursor system prompts by ingesting the external prompt file into the Dojo MemoryStore via the gateway MemoryStore API, which saves the parsed metadata and behavioral indicators as MemoryEntry and MemorySeed objects.

Does ingesting system prompts require any specific dependencies or external libraries?

Ingesting system prompts requires no specific external dependencies, as the skill operates independently to parse prompt files and store them via the gateway MemoryStore API without additional library requirements.

What is the best way to compare multiple AI system prompts for behavioral differences?

The best way to compare multiple AI system prompts is to ingest each prompt into structured memory, extracting ADA disposition indicators like pacing, tone, and initiative, then cross-referencing the stored MemoryEntries to audit behavioral differences.