Generates Python implementations and tests from spec stubs and contracts.
Install
mkdir -p .claude/skills/jaunt && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/17291" && unzip -o skill.zip -d .claude/skills/jaunt && rm skill.zipInstalls to .claude/skills/jaunt
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Use when working with the Jaunt spec-driven code generation framework for Python. Trigger for requests mentioning Jaunt, @jaunt.magic, @jaunt.test, spec stubs, jaunt build, jaunt test, jaunt.toml, __generated__ directories, or writing specs/tests that Jaunt will generate implementations for. Also use when the user wants to set up a new Jaunt project, configure LLM providers, debug build failures, or understand the spec-driven development workflow.Key capabilities
- →Generate Python implementations from `@jaunt.magic` stubs
- →Generate pytest tests from `@jaunt.test` stubs
- →Provide project-aware instructions for Jaunt workflows
- →Support spec-driven development
- →Configure LLM providers for code generation
How it works
Jaunt processes spec stubs marked with `@jaunt.magic` or `@jaunt.test` to generate corresponding Python code and pytest suites. It uses the OpenAI Codex CLI for this generation.
Inputs & outputs
When to use jaunt
- →Generating code from specs
- →Running Jaunt build loops
- →Validating contract implementations
About this skill
Jaunt (spec-driven code generation)
Jaunt is a spec-driven code generation framework for Python: you write intent as
@jaunt.magic / @jaunt.test / @jaunt.contract stubs and Jaunt generates real
implementations and pytest tests into __generated__/ using the OpenAI Codex CLI.
Get the current workflow primer
Jaunt ships its own always-current, project-aware agent briefing. Run it and load the output into context before working:
jaunt instructions # markdown primer + a live snapshot of THIS project
jaunt instructions --json # {command, ok, text, project} for tooling/MCP
jaunt instructions is the single source of truth for how to author specs, run
the build/test loop, read build status, and use contract mode. This file is kept
intentionally thin so it cannot drift from the installed CLI.
Hard rules (if you cannot run the CLI)
- Never edit files under
__generated__/— they are overwritten on every build. - Never hand-write the body of a
@jaunt.magicsymbol. The docstring is the contract and Jaunt fills in the code; keep the body araise RuntimeError(...)stub. - Pair every
@jaunt.magicspec with@jaunt.testcoverage.
When not to use it
- →When working with files under `__generated__/` as they are overwritten
- →When hand-writing the body of a `@jaunt.magic` symbol
- →When not using the Jaunt framework for Python code generation
Limitations
- →Files under `__generated__/` are overwritten on every build
- →Cannot hand-write the body of a `@jaunt.magic` symbol
- →Requires pairing every `@jaunt.magic` spec with `@jaunt.test` coverage
How it compares
This skill automates the creation of Python implementations and tests from high-level specifications, contrasting with manual coding and test writing for each feature.
Compared to similar skills
jaunt side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| jaunt (this skill) | 0 | 27d | Review | Intermediate |
| adk-engineer | 3 | 10d | Review | Advanced |
| unit-testing-test-generate | 2 | 3mo | Review | Intermediate |
| playwright-roll | 2 | 1mo | Review | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
You might also like
adk-engineer
jeremylongshore
Execute software engineer specializing in creating production-ready ADK agents with best practices, code structure, testing, and deployment automation. Use when asked to "build ADK agent", "create agent code", or "engineer ADK application". Trigger with relevant phrases based on skill purpose.
unit-testing-test-generate
sickn33
Generate comprehensive, maintainable unit tests across languages with strong coverage and edge case focus.
playwright-roll
microsoft
Roll Playwright Python to a new version
api-test-generator
mikopbx
Генерация полных Python pytest тестов для REST API эндпоинтов с валидацией схемы. Использовать при создании тестов для новых эндпоинтов, добавлении покрытия для CRUD операций или валидации соответствия API с OpenAPI схемами.
designing-tests
CloudAI-X
Designs and implements testing strategies for any codebase. Use when adding tests, improving coverage, setting up testing infrastructure, debugging test failures, or when asked about unit tests, integration tests, or E2E testing.
test-coverage-improver
openai
Improve test coverage in the OpenAI Agents Python repository: run `make coverage`, inspect coverage artifacts, identify low-coverage files, propose high-impact tests, and confirm with the user before writing tests.