Preflight agent specs for prompt-injection risk across prompt, tool, and architecture layers with Prompt Hardener

Describe an agent in agent_spec.yaml, run deterministic prompt-injection analysis, generate mitigations, and validate defenses before rollout.

Prerequisites

Python 3, pipx or uv optional

Installation

Use the upstream install or setup path that matches your environment:

• pipx install https://github.com/cybozu/prompt-hardener/releases/download/v0.6.0/prompt_hardener-0.6.0-py3-none-any.whl
• Recommended if you already use uv for Python tooling.
• uv tool install https://github.com/cybozu/prompt-hardener/releases/download/v0.6.0/prompt_hardener-0.6.0-py3-none-any.whl
• pip install https://github.com/cybozu/prompt-hardener/releases/download/v0.6.0/prompt_hardener-0.6.0-py3-none-any.whl

Requirements and caveats from upstream:

• Deterministic first: init, validate, analyze, report, and diff do not require an LLM API key
• Use this if you prefer a standard Python environment.

Basic usage or getting-started notes:

• run deterministic security analysis across prompt, tool, and architecture layers

• Choose the installation method that fits how you want to use Prompt Hardener.

• Using pipx

• Source: https://github.com/cybozu/prompt-hardener

• Extracted from upstream docs: https://raw.githubusercontent.com/cybozu/prompt-hardener/HEAD/README.md

Documentation

• https://github.com/cybozu/prompt-hardener

Source

• Agent Skill Exchange