Create and structure a new autonomous project — "/new-project <what project does>"
Create an autonomous project workspace using memory_write and mission_create.
Given the user's description of what the project does, derive a short slug (lowercase, hyphens, e.g. ai-research). Then execute these steps sequentially (one tool call at a time — do NOT batch calls that depend on each other):
memory_write(target: "projects/{slug}/AGENTS.md", content: "# {Project Name}\n\n{What the agent should know about this project: domain, stakeholders, priorities, constraints, tools/APIs to use.}")
This file is loaded into the system prompt for every mission in this project. Make it specific and actionable.
memory_write(target: "projects/{slug}/context.md", content: "# {Project Name} — Context\n\n## Overview\n{What the project is and why it exists.}\n\n## Current State\n{What is known so far.}")
memory_write(target: "projects/{slug}/goals.md", content: "# Goals\n\n- Goal 1\n- Goal 2\n...")
Include measurable targets when possible. If the project would benefit from tracked metrics, add a metrics section:
## Metrics
| Metric | Unit | Target | How to measure |
|--------|------|--------|----------------|
| {name} | {unit} | {target} | {evaluation instruction — tell the agent HOW to check this: API call, file to read, command to run} |
Create recurring missions scoped to the project. Use the project name or slug as project_id (the engine resolves it to the correct project):
mission_create(name: "...", goal: "...", cadence: "daily", project_id: "{Project Name}")
Choose appropriate cadences: hourly, daily, weekly, monthly, or cron expressions like 0 9 * * 1-5.
projects/
{slug}/
AGENTS.md # Agent instructions (loaded into system prompt)
context.md # Background knowledge, current state
goals.md # Goal breakdown with optional metrics
research/ # Research and analysis outputs
reports/ # Generated reports
project_id when creating missions. Without it, missions land in the Default project.