Works with the AI tools you already use
Legacy Code Characterization Test Builder
by heyhridyansh
Build a behavioral safety net for legacy code to ensure stable refactoring and migrations.
$11.99
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See it in action
You say
Create a characterization test plan for this legacy Java billing service before we migrate it to Spring Boot. I need to ensure the tax calculation quirks and DB side effects are preserved.
Your agent does
Refactoring Safety Matrix
- Behavior: Tax rounding quirk (half-up)
- Test:
testTaxRoundingHistoricalQuirk - Layer: Unit
- Known Bug: Yes (Accidental)
- Must Stay Stable: Yes
Preconditions
- Capture DB write ordering for audit logs.
- Map all null-check fallbacks.
What you get
About this skill
The problem
Refactoring legacy code without a safety net often leads to regression bugs, especially when side effects and edge cases are undocumented. Relying on existing tests is risky when they are brittle, over-mocked, or only cover happy paths.
What it does
- Identifies and inventories observable legacy behavior including side effects, state changes, and error handling.
- Classifies behavior into contractual, accidental, and known bugs to prioritize what must stay stable.
- Maps complex input boundaries like nulls, legacy formats, and permission variants.
- Generates a refactoring safety matrix that labels known quirks instead of fixing them prematurely.
- Designs or implements characterization tests using your existing framework and repository conventions.
Why this beats prompting it yourself
Generic prompts often try to "fix" or "clean up" code during test generation, which hides current behavior. This skill strictly enforces the separation of characterization from refactoring, ensuring you capture exactly what the system does today, including its historical quirks and bugs.
Use cases
- Building a regression suite before migrating a monolith to microservices.
- Locking down behavior before replacing a core third-party dependency.
- Documenting and protecting a risky, undocumented module before cleanup.
- Capturing current API responses to ensure a rewrite maintains the contract.
Known limitations
Does not execute tests or verify passes without environment access. It will not automatically fix production bugs or guarantee 100% behavioral capture for non-deterministic systems.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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Creator
24 skills on Agensi
I create practical, AI-ready skills for Cursor, Claude Code, Codex CLI, Replit, and other agents that support the SKILL.md format. My skills focus on specific business and workflow problems, including ecommerce creative audits, design quality checks, prompt and skill validation, content systems, and process automation. Each skill is built with clear inputs, structured outputs, defined permissions, safeguards, and real-world usability.
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