docs: rewrite usage.md to the current gateway model

usage.md described a pre-gateway operating model — a roboco_task_scan
tool, /api/v1/<group> endpoints, an awaiting_docs status, and an 18-agent
roster. Update it to the real surface: give_me_work, /api/<group> routes,
awaiting_documentation, the estimated_complexity/task_type/nature task
fields, and 19 agents.
This commit is contained in:
Renn F
2026-06-05 17:20:37 +02:00
parent ecea593a51
commit 8596c72d9b
+43 -20
View File
@@ -4,7 +4,7 @@ Operating the AI company after deployment.
## The Organization ## The Organization
18 AI agents organized as a company: 19 AI agents organized as a company:
``` ```
CEO (You) CEO (You)
@@ -15,7 +15,7 @@ CEO (You)
└── Main PM └── Main PM
├── Backend Cell (PM, 2 Devs, QA, Documenter) ├── Backend Cell (PM, 2 Devs, QA, Documenter)
├── Frontend Cell (PM, 2 Devs, QA, Documenter) ├── Frontend Cell (PM, 2 Devs, QA, Documenter)
└── UX/UI Cell (PM, Dev, QA, Documenter) └── UX/UI Cell (PM, 2 Devs, QA, Documenter)
``` ```
## Agent IDs ## Agent IDs
@@ -63,7 +63,7 @@ uv run python -m roboco.cli --spawn \
```bash ```bash
# Via API # Via API
curl http://localhost:8000/api/v1/orchestrator/status | jq curl http://localhost:8000/api/orchestrator/status | jq
# Via Docker # Via Docker
docker ps --filter "name=roboco-agent" docker ps --filter "name=roboco-agent"
@@ -94,14 +94,24 @@ docker ps --filter "name=roboco-agent" -q | xargs docker stop
## Creating Tasks ## Creating Tasks
`POST /api/tasks` has no silent defaults — `title`, `description` (min 20
chars), `acceptance_criteria` (at least one), `team`, `task_type`, `nature`,
and `estimated_complexity` are all required, plus exactly one of `project_id`
(the repo this task targets) or `product_id` (a cell→project map for a fan-out
task). See the `TaskCreate` schema in `roboco/models/task.py` (or the Swagger
UI at `/docs`) for the full field list and enum values.
```bash ```bash
curl -X POST http://localhost:8000/api/v1/tasks \ curl -X POST http://localhost:8000/api/tasks \
-H "Content-Type: application/json" \ -H "Content-Type: application/json" \
-d '{ -d '{
"title": "Implement user authentication", "title": "Implement user authentication",
"description": "Add JWT-based auth to the API", "description": "Add JWT-based auth to the API endpoints",
"team": "backend", "team": "backend",
"complexity": "medium", "task_type": "code",
"nature": "technical",
"estimated_complexity": "medium",
"project_id": "<project-uuid>",
"acceptance_criteria": [ "acceptance_criteria": [
"Users can register", "Users can register",
"Users can login", "Users can login",
@@ -110,19 +120,23 @@ curl -X POST http://localhost:8000/api/v1/tasks \
}' }'
``` ```
Enum values: `task_type` ∈ {`code`, `documentation`, `research`, `planning`,
`design`, `administrative`}; `nature` ∈ {`technical`, `non_technical`};
`estimated_complexity` ∈ {`low`, `medium`, `high`}.
## Task Lifecycle ## Task Lifecycle
``` ```
pending → claimed → in_progress → verifying → awaiting_qa → awaiting_docs → completed pending → claimed → in_progress → verifying → awaiting_qa → awaiting_documentation → completed
blocked/paused blocked/paused
``` ```
Agents automatically: Agents automatically:
1. Scan for pending tasks (`roboco_task_scan`) 1. Pull pending work via the gateway verb `give_me_work()`
2. Claim tasks they can work on 2. Claim it with `i_will_work_on(task_id)` (auto-creates the feature branch)
3. Follow the workflow: UNDERSTAND → PLAN → EXECUTE → VERIFY → NOTES 3. Follow the workflow: UNDERSTAND → PLAN → EXECUTE → VERIFY → NOTES
4. Submit for QA when done 4. Open a PR and submit for QA when done (`open_pr` / `i_am_done`)
5. Move to next task 5. Move to next task
## API Endpoints ## API Endpoints
@@ -131,10 +145,10 @@ Agents automatically:
|----------|-------------| |----------|-------------|
| `GET /health` | Health check | | `GET /health` | Health check |
| `GET /docs` | Swagger UI | | `GET /docs` | Swagger UI |
| `GET /api/v1/orchestrator/status` | Agent states | | `GET /api/orchestrator/status` | Agent states |
| `GET /api/v1/tasks` | List tasks | | `GET /api/tasks` | List tasks |
| `POST /api/v1/tasks` | Create task | | `POST /api/tasks` | Create task |
| `GET /api/v1/tasks/{id}` | Task details | | `GET /api/tasks/{id}` | Task details |
## Viewing the API ## Viewing the API
@@ -158,10 +172,19 @@ uv run python -m roboco.cli --spawn main-pm be-dev-1 be-qa
### Create and Monitor a Task ### Create and Monitor a Task
```bash ```bash
# Create task # Create task (all fields below are required — see POST /api/tasks schema)
curl -X POST http://localhost:8000/api/v1/tasks \ curl -X POST http://localhost:8000/api/tasks \
-H "Content-Type: application/json" \ -H "Content-Type: application/json" \
-d '{"title": "Fix login bug", "team": "backend", "complexity": "trivial"}' -d '{
"title": "Fix login bug",
"description": "Login fails on expired-token refresh path",
"team": "backend",
"task_type": "code",
"nature": "technical",
"estimated_complexity": "low",
"project_id": "<project-uuid>",
"acceptance_criteria": ["Expired token refreshes without 500"]
}'
# Watch agent pick it up # Watch agent pick it up
docker logs -f roboco-agent-be-dev-1 docker logs -f roboco-agent-be-dev-1
@@ -183,7 +206,7 @@ docker compose down
### Start Small ### Start Small
Don't spawn all 18 agents at once. Start with: Don't spawn all 19 agents at once. Start with:
1. `main-pm` alone - verify spawning works 1. `main-pm` alone - verify spawning works
2. Add `be-dev-1` - verify task claiming 2. Add `be-dev-1` - verify task claiming
3. Add `be-qa` - verify full workflow 3. Add `be-qa` - verify full workflow
@@ -192,7 +215,7 @@ Don't spawn all 18 agents at once. Start with:
```bash ```bash
# Quick status # Quick status
curl -s http://localhost:8000/api/v1/orchestrator/status | jq '.agents' curl -s http://localhost:8000/api/orchestrator/status | jq '.agents'
# Detailed container info # Detailed container info
docker inspect roboco-agent-be-dev-1 docker inspect roboco-agent-be-dev-1
@@ -213,7 +236,7 @@ docker logs -f roboco-agent-be-dev-1
Each agent container uses ~500MB-2GB RAM depending on context. With 128GB RAM: Each agent container uses ~500MB-2GB RAM depending on context. With 128GB RAM:
- 3 agents: ~6GB - 3 agents: ~6GB
- 6 agents: ~12GB - 6 agents: ~12GB
- 18 agents: ~36GB - 19 agents: ~38GB
Monitor with: Monitor with:
```bash ```bash