subagent-spawning

Claude Code skill for spawning customized subagents with full MCP tool access — replaces dare-agents MCP with pure markdown orchestration.

• 🤖 Role-specific subagents — spawn specialized thinking agents from SOP definitions
• 🔧 Full tool inheritance — each subagent gets all MCP tools (literature search, web browsing, citation tracing)
• 📝 Pure markdown — zero code, zero dependencies, zero runtime processes
• 🎯 Opus-level reasoning — subagents operate at the same quality as the main orchestrator

What is this?

This is a Claude Code skill that standardizes how subagents are spawned during research workflows. When an SOP declares execution: subagent, this skill tells main CC exactly how to create that subagent — what model to use, what tools to give it, how to pass inputs, and how to handle outputs.

Designed for the NOESYNTH/DARE research engine ecosystem. Works alongside literature-engine, web-browsing, and semantic-scholar-mcp.

How It Works

SOP SKILL.md declares: execution: subagent, prompt: ./prompt.md
  → Main CC reads prompt.md (role definition)
  → Main CC loads spawn-agent skill (execution rules)
  → Main CC invokes Agent tool:
      - prompt = [prompt.md] + [input parameters]
      - model = opus (default)
      - tools = all (inherited)
  → Subagent executes with full MCP access
  → Returns markdown result

Default Strategy

Dimension	Default	Rationale
Model	opus	Quality-first; same reasoning power as main CC
Tools	all	Subagent autonomously decides what to use
Output	markdown	Natural, structured, no parsing needed

Quick Start

1. Install Skill

Clone this repository:

git clone https://github.com/yogsoth-ai/subagent-spawning.git

2. Write an SOP with Subagent

In your SOP's SKILL.md frontmatter:

---
execution: subagent
prompt: ./prompt.md
input: idea (string), context (string)
output: markdown (analysis with variants)
---

Create a prompt.md next to it defining the subagent's role.

3. Consult RULES.md

See skills/spawn-agent/RULES.md for the full authoring guide with examples.

SOP Declaration Format

---
name: SCAMPER Substitute
description: Apply Substitute lens to generate idea variants
type: sop
layer: sop
execution: subagent
prompt: ./prompt.md
input: idea (string), context (string)
output: markdown (variants with title, description, novelty assessment)
---

Field	Purpose
execution: subagent	Signals spawn-agent skill activation
prompt: ./prompt.md	Relative path to role prompt file
input	Documents what parameters the SOP receives
output	Documents expected output structure

Project Structure

subagent-spawning/
├── skills/
│   └── spawn-agent/
│       ├── SKILL.md      # Runtime — loaded by CC when executing subagent SOPs
│       └── RULES.md      # Authoring reference — how to write subagent SOPs
├── assets/
│   └── repo-info.txt
├── README.md
├── .gitignore
└── LICENSE

What This Replaces

Before (dare-agents MCP)	After (subagent-spawning)
34 TypeScript tool files	0 code files
34 zod schemas	0 schemas
pi-ai + OpenRouter dependency	None
MCP server process	None
Information-isolated execution	Full MCP tool access
~2000 lines TypeScript	~200 lines markdown

Links

• 🐙 GitHub repository
• 📚 literature-engine
• 🌐 web-browsing
• 🔬 semantic-scholar-mcp

Version

v0.1.0 — Initial release (spawn-agent skill + authoring rules)

📄 License

Apache-2.0