New to Claude Skills? Learn how to install them →

Hplastic-labs on GitHub

Honcho Verifier

Free

Easily verify changes in your Honcho stack.

Get this skill

Free · Opens the source repo

What Honcho Verifier does

The Honcho Verifier skill allows developers to efficiently build, launch, and interact with a local Honcho stack to verify changes in real-time. This skill is particularly useful for confirming that code modifications work as intended within the application, especially when working with the /v3 HTTP API and the deriver queue. By leveraging Docker Compose, users can quickly set up the necessary environment, which includes services like Postgres and Redis, to ensure a seamless testing experience.

To get started, users must ensure that Docker Compose is installed and running. The skill provides clear instructions on how to check the status of the stack and how to launch it if needed. Developers can run their branch's code alongside the existing stack without the need for a full image rebuild, which saves time and avoids potential conflicts. Furthermore, the skill emphasizes the importance of verifying changes across multiple surfaces, including CLI, SDKs, and REST endpoints, ensuring comprehensive testing of any modifications made.

Configuration management is a critical aspect of using the Honcho Verifier. The skill outlines how to manage environment variables and configuration files to control API keys and other settings effectively. This flexibility allows developers to customize their testing environment according to their specific needs. Additionally, the skill supports running various test suites locally, enabling developers to validate their changes against real API keys and configurations, which is essential for maintaining the integrity of the application.

Overall, the Honcho Verifier skill is designed for developers looking to streamline their testing processes within the Honcho framework. It provides a structured approach to verifying code changes, ensuring that developers can maintain high-quality standards in their applications while minimizing the overhead associated with testing.

When to use it

Use this skill when you need to verify changes in your Honcho application during development or testing phases.

When not to use it

This skill may not be suitable for users who do not work with the Honcho stack or prefer a different testing framework.

What you can build with it

Verifying API Changes

When updating API endpoints or schemas, use this skill to ensure all surfaces are functioning correctly.

Testing Configuration Changes

Make configuration changes and verify their impact on the application behavior using the Honcho Verifier.

Running Local Tests

Utilize the skill to run unit and integration tests locally, ensuring that all modifications are validated before deployment.

How to install Honcho Verifier

View source

1. Install with the skills CLI

npx skills add plastic-labs/honcho/verify --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by plastic-labs

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.

Drive it

Prefer driving through the honcho-cli skill; fall back to the SDKs (sdks/python, sdks/typescript), then raw REST against /v3, in that order when a method isn't available at the higher level. The honcho-integration skill covers how to use the SDKs.

When a change updates endpoints or makes schema changes, verify across all three surfaces — CLI, SDKs, and REST — since they can drift independently.

For LLM-path changes, the fastest synchronous surface is dialectic at the minimal reasoning level: send a couple of messages, then hit /v3/.../peers/{peer_id}/chat and observe the response.

Configuration

Configuration is central to both driving the app and running tests: it's how API keys reach the server and how a config-related change gets exercised at all. Settings come from environment variables or files, with precedence env > .env > config.toml > defaults. To verify a configuration change, set the relevant option through one of these layers, restart the affected process, and observe the behavioral difference at the surface — the same mechanism lets you point provider base URLs, model choices, and timeouts at credentials and proxies you actually have.

Two concrete levers: deep-nested settings (e.g. [dialectic.levels.minimal.model_config.overrides.provider_params]) are miserable as env vars — drop a partial config.toml in the repo root instead. And for load-time config behavior, uv run python -c "import src.config; ..." is faster than booting the server.

Test suites

Three test types matter here. All run in CI, but they're also runnable locally with whatever API keys and configuration you have — Honcho's config surface is large, so options like per-agent timeouts and provider base URLs can be pointed at your own keys/proxies to exercise a change:

# Unit tests (pytest; spins up its own infra via fixtures)
uv run pytest tests/

# Unified tests — step-based end-to-end flows defined in JSON
# (config hierarchy, multi-turn interactions, LLM-as-judge assertions)
uv run python -m tests.unified.run
uv run python -m tests.unified.run --test-dir tests/unified/test_cases

# Live LLM tests — real provider calls, for testing specific backends.
# Needs provider API keys AND model vars — without LIVE_LLM_*_MODELS the
# tests silently deselect that provider. See tests/live_llm/README.md.
export LLM_ANTHROPIC_API_KEY=...
export LIVE_LLM_ANTHROPIC_45_PLUS_MODELS=claude-sonnet-4-5
uv run pytest tests/live_llm -n 0 --live-llm --no-header -q

Frequently asked questions about Honcho Verifier

Similar skills