Generate Test Cases From Your Requirements
Generic AI writes generic tests: plausible steps for software it has never seen. An agent on the BesTest MCP reads your actual requirements, acceptance criteria, and coverage before it writes a word. That difference is the whole point.
The blank page after every requirement
Every requirement eventually needs test cases, and drafting them is the same translation work each time: read the acceptance criteria, imagine the paths, write the steps. Skip it and coverage gaps pile up; rush it and the tests check the happy path only.
ChatGPT can draft test cases, but it drafts them blind: it has never read your requirement, your conventions, or what is already covered. Connected over MCP, the agent drafts from your actual data and files the results as linked, reviewable drafts.
Drafting blind
- Read the requirement, stare at the blank test case form
- Paste text into a chatbot, copy results back by hand, unlinked
- Get plausible steps that ignore what is already covered
- Coverage gaps wait for whoever has a free afternoon
Drafting grounded
- The agent reads the requirement and its acceptance criteria first
- It checks existing coverage, so it drafts what is missing, not duplicates
- Drafts land in BesTest as linked test cases, ready for review
- Your review workflow, with its review audit trail, keeps humans in charge
One prompt, start to finish
For every requirement in the payments folder with no linked test case, draft one from its acceptance criteria, link it to the requirement, and leave it in draft for review.- 1
Finds the real gaps
It lists the requirements in scope and checks their coverage over the MCP, so it drafts for what is actually missing instead of duplicating existing work.
- 2
Drafts from your requirements, not from vibes
Steps and expected results come from each requirement’s acceptance criteria, and significance guides depth: your riskiest requirements deserve more than a happy path.
- 3
Files drafts for humans to judge
Every generated test case lands linked to its requirement, in draft, routed through the built-in review workflow. The review audit trail records who reviewed and approved what.
The result
Drafting stops being the bottleneck: gaps get filled the day they appear, every draft arrives linked and reviewable, and your test library grows in your conventions instead of a chatbot’s.
Drafts land in review, in your folder conventions, linked to the requirement they came from.
More prompts to steal
Draft edge-case tests for REQ-88: think beyond the happy path and list your assumptions.
Turn this bug report into a regression test case and link it to the related requirement.
Review the payments folder: which existing test cases look outdated against their requirements?
Scoped to your permissions, granted per user
Your agent acts as you: everything it reads or writes stays inside your Jira permissions. The MCP is in closed beta while we harden it, with GA coming. The request form asks for a few details from BesTest’s Project Settings in your Jira, which is what lets us enable exactly your site and user.
Request beta accessFrequently asked questions
Will it flood us with low-quality tests?
It drafts into your normal review gate, not into your runs: with reviews set to required, nothing counts until a human approves it. Generation makes drafts cheap; the review workflow keeps the bar exactly where you set it.
How is this better than pasting into ChatGPT?
Context and filing. The agent reads the actual requirement, the related test cases, and current coverage before drafting, and the output lands linked in BesTest instead of in a chat window you copy from. Same model intelligence, very different groundedness.
Can it also generate automated tests?
Yes: the same requirement context can drive Playwright or any framework, with the code landing in your repo while the linked test cases land in BesTest. See the AI testing hub for that flow.
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