agent-builder

The platform's own meta-agent. Generates, tests, and deploys new a2a-pack agents from a natural-language description.

What it does

The single build(name, prompt) skill:

1. Builds an inner deepagents LangGraph configured with project tools and packaged builder skills:
   • deepagent-agent-design — when to use DeepAgents skills, subagents, workspace backends, and deterministic tools
   • a2apack-agent-authoring — how to shape agent.py, public @skill schemas, runtime metadata, pricing, resources, and auth
   • deepagents-implementation-patterns — concrete create_deep_agent wiring for ctx.llm credentials, skills, tools, and subagents
   • workspace-artifact-safety — workspace grants, artifacts, bounded subprocesses, and scope expansion
   • agent-quality-review — pre-sandbox and pre-deploy checks for generated agents
   • list_agent_files(name) / write_agent_file(name, path, content) / read_agent_file(name, path) — boto3 → MinIO, scoped to agents/<name>/ in the caller's workspace
   • write_agent_skill(...) — creates valid DeepAgents skills/<skill-name>/SKILL.md bundles for generated agents, so rich behavior lives in progressive-disclosure skills instead of fake tools
   • init_agent_template(name, description, frontend="react"|"static"|"none") — starts from the current a2a-pack scaffold and can include packed frontend templates under frontend/ for app-like agents
   • test_agent_in_sandbox(name) — tarballs the workspace project, spins a microVM with the public a2a-pack wheel installed, runs a2a card to verify the scaffold is valid, and prints frontend metadata when a packed app is declared
   • cp_deploy_tarball(name, version, public) — POSTs the tarball to /v1/agents/from-tarball on the user's behalf using their forwarded CP JWT
   • cp_deploy_source_repo(name) — POSTs the current managed source repo to /v1/agents/{name}/source/deploy when source edits already live in Gitea
2. Streams the graph's tool calls back to the dashboard as agent_progress events (so the user watches the build happen in real time, not in silence).
3. Returns the live URL when the new agent finishes deploying.

What it needs forwarded

Three platform-managed bits land on the inner skill via RunContext:

Field	Source	Required?
ctx.workspace.bucket	grant minted by the orchestrator	yes
ctx.llm	caller's saved LLM credential, routed by the platform (Card declares llm_provisioning=platform)	yes
ctx.cp_jwt	caller's CP JWT (Card declares wants_cp_jwt=True)	yes — used by cp_deploy_tarball

The user opts into all three when they pick agent-builder from the marketplace — the dashboard already surfaces these on the agent card.

Pricing

$0.10 / call during the current pricing model. The builder uses your saved LLM credential. The deployed agent is yours forever; subsequent invocations of a generated LLM agent also use the caller's saved LLM credential via ctx.llm.

How to call it

In the dashboard chat (Workspace tab):

use agent-builder.build to make a new agent named "csv-sanitizer" that takes a CSV path, strips whitespace from every column, deduplicates rows, and writes the cleaned file back next to the original

The orchestrator will discover agent-builder, hand off with the required forwards, you'll watch the inner deepagents scaffold + test + deploy in real time, then get a live URL.

Local dev

cd apps/agent-builder
python3 -m venv .venv
.venv/bin/pip install -e ../a2a -r requirements.txt
.venv/bin/a2a card                # see what the Card looks like
.venv/bin/a2a validate

You can't run the full skill locally without a workspace bucket + CP JWT — those come from the platform at invoke time.