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deep-agents-core

Bootstrap Deep Agents applications using create_deep_agent and SKILL.md frontmatter.

3|1|Updated Jun 4, 2025
Search Tags:#configuration#frontmatter#bootstrapping#skill-loading#harness#deep-agents
One-click install
npx skills add https://github.com/jillesca/sp_oncall --skill deep-agents-core-jillesca
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: deep-agents-core
Source: https://github.com/jillesca/sp_oncall/tree/main/.agents/skills/deep-agents-core
Command: npx skills add https://github.com/jillesca/sp_oncall --skill deep-agents-core-jillesca

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Guides developers in building any Deep Agents application by detailing how to use create_deep_agent(), the harness architecture, and the SKILL.md format. It also covers common configuration options to standardize setup across projects.

Core Features & Use Cases

  • Entry-point guidance: explains the required frontmatter in SKILL.md and how skills are loaded on demand.
  • Harness & workflow clarity: outlines the overall orchestration pipeline and how subagents interact.
  • Configuration patterns: provides recommended settings for backends, memory, and persistence across runs.

Quick Start

Explain how to bootstrap a Deep Agents project using create_deep_agent and the core harness configuration.

Frequently Asked Questions about deep-agents-core

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

FAQPage Schema
How do I bootstrap a Deep Agents project and configure the core harness?▼

Bootstrapping a Deep Agents project involves invoking create_deep_agent() and defining the core harness configuration to establish the orchestration pipeline and subagent interactions for scalable agent systems.

What is the SKILL.md format and how does frontmatter drive skill loading?▼

The SKILL.md format uses required frontmatter to define metadata, enabling on-demand skill loading across harnessed workflows and standardizing configuration setup throughout Deep Agents projects.

How does the Deep Agents harness architecture orchestrate subagent workflows?▼

The harness architecture orchestrates subagent workflows via a structured pipeline, managing interactions and ensuring scalable agent systems execute harnessed workflows consistently across project runs.

What configuration patterns are recommended for Deep Agents backends and memory?▼

Recommended configuration patterns for Deep Agents include standardizing settings for backends, memory, and persistence across runs, enforcing production-ready practices for scalable and consistent agent system behavior.

Do I need specific frontmatter in SKILL.md to ensure production-ready Deep Agents setup?▼

Yes, clear frontmatter in SKILL.md is required to ensure production-ready Deep Agents setup, enforcing documented configuration options and standardized skill loading patterns across scalable agent projects.

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