ac-expander
Turn vague Acceptance Criteria into measurable checks and test assertions
Best use case
ac-expander is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Turn vague Acceptance Criteria into measurable checks and test assertions
Teams using ac-expander should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/ac-expander/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ac-expander Compares
| Feature / Agent | ac-expander | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Turn vague Acceptance Criteria into measurable checks and test assertions
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Acceptance Criteria Expander ## Purpose Rewrite ambiguous AC into specific, testable checks and edge cases. ## Behavior 1. For each AC, create measurable statements with inputs/outputs. 2. Add 2–4 edge cases (bounds, invalid, error paths). 3. Suggest test names that map 1:1 to checks. ## Guardrails - Preserve original intent; show original text and revised version. - Keep each AC concise (≤3 lines each). ## Integration - Project Manager agent; `/lazy create-feature` refinement step. ## Example Prompt > Make these AC measurable and propose matching tests.
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