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Direct Tests

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internet-court
direct-tests

Write and run fast direct mode tests for GenLayer intelligent contracts.

Overview

Publisherinternet-court
Repositoryinternet-court-skill
Skill namedirect-tests
Stars
5.8K
Forks
106
Bundled files
1
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  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by internet-court on GitHub. Read the source before you install it.

Installation

Install the Direct Tests AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/internet-court/internet-court-skill.git /tmp/internet-court-skill
mkdir -p .claude/skills
cp -r /tmp/internet-court-skill/vendored/genlayer/direct-tests .claude/skills/direct-tests
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Direct Tests in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Direct Tests on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Direct Tests is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Direct Mode Tests

Write fast, in-memory tests for intelligent contracts. No server, no Docker — tests run in ~30-50ms.

Running Tests

bash
pytest tests/direct/ -v
pytest tests/direct/test_specific.py -v
pytest tests/direct/test_specific.py::test_one_case -v

Fixtures

Available from genlayer-test pytest plugin:

python
def test_example(direct_vm, direct_deploy, direct_alice, direct_bob):
    # direct_vm      — VMContext with cheatcodes
    # direct_deploy  — deploy a contract file
    # direct_alice   — test address
    # direct_bob     — test address
    pass

All fixtures: direct_vm, direct_deploy, direct_alice, direct_bob, direct_charlie, direct_owner, direct_accounts

Basic Test Pattern

python
def test_set_and_get(direct_vm, direct_deploy, direct_alice):
    contract = direct_deploy("contracts/my_contract.py")
    direct_vm.sender = direct_alice

    contract.set_data("hello")

    result = contract.get_data(direct_alice)
    assert result == "hello"

Mocking Web Requests

For contracts that call gl.nondet.web.get():

python
import json

def test_with_web_mock(direct_vm, direct_deploy, direct_alice):
    contract = direct_deploy("contracts/my_contract.py")
    direct_vm.sender = direct_alice

    # Pattern: regex matching on URL
    direct_vm.mock_web(
        r".*api\.example\.com/prices.*",
        {"status": 200, "body": '{"price": 42.5}'},
    )

    contract.update_price("ETH/USD")
    assert contract.get_price("ETH/USD") == 42.5

Full mock format (when you need headers/method control)

python
direct_vm.mock_web(
    r"api\.example\.com/data",
    {
        "response": {
            "status": 200,
            "headers": {},
            "body": json.dumps({"key": "value"}).encode()
        },
        "method": "GET"
    }
)

Mocking LLM Responses

For contracts that call gl.nondet.exec_prompt():

python
direct_vm.mock_llm(
    r".*Extract the match result.*",  # Regex on prompt text
    json.dumps({"score": "2:1", "winner": 1}),
)

Clearing Mocks

python
direct_vm.clear_mocks()  # Reset between test scenarios

VMContext Cheatcodes

python
# Set transaction sender
direct_vm.sender = direct_alice

# Set native value (wei)
direct_vm.value = 1000000000000000000  # 1 ETH

# Expect a revert
with direct_vm.expect_revert("Insufficient balance"):
    contract.withdraw(1000)

# Temporary sender change
with direct_vm.prank(direct_bob):
    contract.method()  # Called as bob

# Snapshot and restore state
snap_id = direct_vm.snapshot()
contract.modify_state()
direct_vm.revert(snap_id)  # State restored

# Set account balance
direct_vm.deal(direct_alice, 1000000000000000000)

# Time travel
direct_vm.warp("2024-06-01T12:00:00Z")

Test Organization

tests/direct/
├── conftest.py           # Shared fixtures and mock helpers
├── test_<feature>.py     # Tests per feature/method
└── test_<feature>_web.py # Tests requiring web/LLM mocks

What to Test in Direct Mode

CategoryExample
State transitionsCreate → read back → verify fields
Validation / revertsInvalid inputs, unauthorized callers
Access controlOwner-only methods, role checks
Edge casesEmpty state, boundary values, overflow
Web/LLM parsingMock responses → verify extraction logic

Common Patterns

Testing access control

python
def test_only_owner(direct_vm, direct_deploy, direct_alice, direct_bob):
    contract = direct_deploy("contracts/my_contract.py")

    direct_vm.sender = direct_alice
    contract.create_item("item_1")

    direct_vm.sender = direct_bob
    with direct_vm.expect_revert("Only owner"):
        contract.delete_item("item_1")

Testing state transitions

python
def test_state_flow(direct_vm, direct_deploy, direct_alice):
    contract = direct_deploy("contracts/my_contract.py")
    direct_vm.sender = direct_alice

    contract.create_item("item_1")
    assert contract.get_item("item_1")["status"] == "pending"

    contract.approve_item("item_1")
    assert contract.get_item("item_1")["status"] == "approved"

Reusable mock helpers (conftest.py)

python
import json

def mock_price_api(direct_vm, pair: str, price: float):
    """Mock a price API response."""
    direct_vm.mock_web(
        rf".*api\.example\.com/prices/{pair}.*",
        {"status": 200, "body": json.dumps({"price": price})},
    )

Tips

  • Always direct_vm.sender = ... before calling write methods
  • Use --json flag on genvm-lint check before writing tests to understand the contract's interface
  • Direct mode runs leader function only — validator logic is not exercised. Use integration tests for full consensus validation.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Direct Tests AI skill do?

Write and run fast direct mode tests for GenLayer intelligent contracts.

Why use Direct Tests on TypingMind?

Because you install it once and use it with any model. Direct Tests is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Direct Tests in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/internet-court/internet-court-skill/tree/main/vendored/genlayer/direct-tests. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Direct Tests?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Direct Tests?

As many as you like. As long as a model supports skills, you can use Direct Tests with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Direct Tests AI skill free?

It is published on GitHub by internet-court. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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