Science-backed AI team assembly. From goal to agents to artifacts.
Forge is an open-source system that uses research from DeepMind, PRISM persona science, and context engineering to assemble AI agent teams. It takes a goal, determines whether you need one agent or a team, selects the right coordination topology, and produces structured agent definitions with expert vocabulary, clear deliverables, and anti-pattern guardrails. Works with Claude Code.
The single highest-leverage intervention in AI agent quality is vocabulary routing — using precise domain terminology that activates expert knowledge clusters in the model's embedding space. Real-world job titles and role structures activate relevant training data better than custom personas. And DeepMind's scaling research shows that more agents isn't always better — teams of 3-5 with structured artifact handoffs outperform larger groups.
# Install as a plugin (recommended):
/plugin add https://github.com/jdforsythe/forge
# Or via Vercel's cross-agent installer:
npx add-skill jdforsythe/forge
# Then just describe what you want:
"Build me a SaaS analytics product" # Mission Planner activates
"Create an agent for code review" # Agent Creator activates
forge/
├── .claude-plugin/ Plugin metadata
│ ├── marketplace.json Marketplace definition
│ └── plugin.json Plugin manifest
│
├── skills/ 4 core skills
│ ├── mission-planner/ Decomposes goals into team blueprints
│ ├── agent-creator/ Builds individual agent definitions
│ ├── skill-creator/ Creates reusable skill packages
│ └── librarian/ Manages the agent/template library
│
├── agents/ 3 infrastructure agents
│ ├── verifier.md Validates outputs against schemas
│ ├── researcher.md Gathers context and source material
│ └── reviewer.md Reviews and critiques agent definitions
│
├── library/ Starter collection
│ └── index.json 11 domain agents, 3 team templates
│ ├── software/ Product Manager, Architect, Lead Engineer, QA
│ ├── marketing/ Campaign Strategist, Content Creator, Designer, Analytics Lead
│ └── security/ Lead Auditor, Penetration Tester, Compliance Analyst
│
├── schemas/ Format specifications
│ ├── agent-definition.md 7-component agent structure
│ ├── team-blueprint.md Blueprint format for coordinated teams
│ ├── index-schema.json Library index format
│ └── usage-log-schema.json Usage tracking format
│
├── docs/ User documentation
│ └── research/ Scientific foundation (8 reference documents)
└── ...
Forge uses a 3-level decision flow:
Level 0 — Single Agent. The goal is simple enough for one agent. Forge produces a single well-prompted agent definition with the right vocabulary, deliverables, and guardrails. No coordination overhead.
Level 1 — Known Pattern. The goal matches a template in the library (e.g., SaaS product, marketing campaign, security audit). Forge loads the template, adapts roles to your specific goal, and creates the full agent team with artifact handoff chains.
Level 2 — Novel Domain. No template exists. Forge decomposes the goal into workstreams, proposes a team topology (pipeline, parallel, coordinator, or hierarchical), defines roles with precise vocabulary, and iterates with you until the blueprint is right.
At every level, the same principles apply: real-world role titles, domain-specific vocabulary, structured artifacts between agents, and a hard cap of 3-5 agents per team.
Every design decision in Forge traces back to published research. The docs/research/ directory contains synthesized findings from DeepMind's multi-agent scaling laws, PRISM persona science, and context engineering best practices.
For the full methodology, see METHODOLOGY.md.
- Cowork compatibility: Forge skills fail to run in Cowork. Skills load but stop executing when they attempt to read reference files outside the plugin directory. We are looking for help solving this — PRs welcome! See CONTRIBUTING.md if you want to take a crack at it.
See CONTRIBUTING.md for guidelines on adding agents, templates, skills, and research.