Verify
Build, launch, and drive a local Honcho stack to verify a change at its runtime surface...
Install
npx skills add plastic-labs/honcho --skill verify -g -a claude-code -y- Repository
- plastic-labs/honcho7.9k
- Category
- Engineering
- Updated
- 3d ago
- License
- AGPL-3.0
- Context cost
- Lightabout 1,110 tokens
- Runs scripts
- No, instructions only
What it does
Build, launch, and drive a local Honcho stack to verify a change at its runtime surface (the /v3 HTTP API and the deriver queue). Use when verifying a diff or confirming a change works in the running app.
Verifying changes in Honcho
Prerequisites
Docker Compose is the preferred way to run the stack, docker-compose.yml at
the repo root brings up Postgres (pgvector), Redis, the API server, and the
deriver worker together. If Docker Compose isn't available, the stack can also
run directly on the host (see Launch below); you'll need Postgres with pgvector
and Redis reachable, plus a .env with connection strings and an LLM provider
key for any flow that hits a model (deriver, dialectic, dreamer).
Working in a worktree? It carries neither .env nor node_modules. Copy
.env from the main checkout (that's where the provider keys live), and run
bun install in sdks/typescript if you'll run the full test suite, otherwise the pre-push gate fails on a phantom Cannot find package 'zod'.
Launch
First check whether the stack is already running via Docker Compose:
docker compose ps # look for api / deriver / database / redis
docker compose up -d # start it if not
A running stack is not the same as your branch's code running, check the CREATED column; the images may be weeks old. For verifying a diff, the cheap path is to reuse the stack's Postgres/Redis containers but run the branch's API as a host process on a spare port:
uv run uvicorn src.main:app --port 8901 # branch code, stack's DB/Redis
uv run python -m src.deriver # if the diff touches the worker
This avoids both an image rebuild and the port/project-name conflicts a second
compose stack in a worktree would cause. Without Docker at all, run the two
processes the same way against host Postgres + Redis (API default port 8000
via uv run fastapi dev src/main.py).
When reading server logs, note that with the main .env the telemetry emitter
spams connection warnings at an unreachable endpoint, grep -v telemetry.emitter before looking for the real error.
