skills/agent-repo-init/SKILL.md
One-click initialization of a multi-agent repository from the Antigravity template. Use this skill when users want to scaffold a new project quickly (`quick` mode) or with runtime defaults (`full` mode) including MCP toggle, swarm preference context, sandbox type, and optional git init. LLM configuration is handled later by ag-setup.
npx skillsauth add study8677/antigravity-workspace-template agent-repo-initInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Initialize a new project from this repository template with two modes.
quick: Fast scaffold with clean copy and minimal setup.full: quick plus runtime profile setup (.env, mission, context profile, init report) and optional git init.Use the portable script in this skill directory:
python skills/agent-repo-init/scripts/init_project.py \
--project-name my-agent \
--destination-root /absolute/path \
--mode quick
Full mode example:
python skills/agent-repo-init/scripts/init_project.py \
--project-name my-agent \
--destination-root /absolute/path \
--mode full \
--enable-mcp \
--disable-swarm \
--sandbox-runtime microsandbox \
--init-git
<destination_root>/<project_name>artifacts/logs/agent_repo_init_report.mdsrc/ modulesfull mode, review .context/agent_runtime_profile.md after generation./ag-setup in the generated project to choose and write the LLM endpoint.tools
Bootstraps a new multi-agent repository from the Antigravity template via `init_agent_repo`. Supports quick scaffold and full runtime profile setup including MCP toggle, swarm preference, sandbox type, and optional git init. LLM configuration is handled later by ag-setup.
research
Performs deep research on a topic via `deep_research`. Simulates a multi-step research process and returns a comprehensive research result as a string.
development
High-level deployment wrapper over Antigravity core with graph-first knowledge injection and all-file support. Exposes `refresh_filesystem` and `ask_filesystem` for building and querying the knowledge graph.
tools
Exposes graph-based retrieval as a tool capability via `query_graph`. Reads normalized graph store files, builds a query-relevant subgraph, and returns LLM-friendly semantic triples with replayable evidence metadata.