Generate test scenario coverage from a feature spec — happy paths, edge cases, error handling, accessibility, security, and performance — with a coverage analyzer that flags gaps. Use to define what to test before QA writes the test plan.
SkillScore73Maintained
Automatic
◆QA & Test Engineering pack
Last verified 8/20/2026
What it changes
Passed 16 of 22 test cases with the skill, and 11 of 22 without it.
Without skill50%
With skill73%
Checks it passed that the model alone missed
Recommends 3 to 5 edge case scenarios.
Recommends 2 to 3 happy path scenarios.
Uses the input flag to pass the feature spec file path.
and 5 more in the full report
6 fixed10 passed either way5 still failing1 broke
Pass-rate lift
+23 pp
Tokens
+80%
Agent turns
0%
Response time
+3%
Model gemini-3.6-flashMeasured 8/20/2026v116 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 6
Prompt
We want to run our scenario coverage verification tool against checkout_spec.json and output markdown. Should we execute pytest or use the repository's dedicated python scenario verification script? Provide the exact bash command line to run.
What was checked, without and with the skill
Checked
Without skill
With skill
Specifies test_scenario_generator.py in the command path.
Missed
Passed
Uses the input flag to pass the feature spec file path.
Missed
Passed
case-06 · gemini-3.6-flash · 8/20/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md201 lines5 filesincludes scripts
Test Scenarios
Generate complete scenario coverage from a feature spec before tests
are written. Closes the gap between "we built it" and "it survives
production."
When to use this skill
After PRD approval but before engineering implementation
During sprint planning to size testing effort
During code review to verify test coverage
During QA planning to scope test pass
During bug-bash prep
After a production incident to validate scenario gaps
The 7 scenario categories
For every feature, generate scenarios across:
Happy paths — primary user goals achieved cleanly
Edge cases — boundary conditions, unusual inputs
Error handling — what users see when things go wrong
Localization (RTL, long-string, currency, date format)
Cross-platform (browsers, devices, OS versions)
Clarify First
Before generating scenarios, confirm these inputs. If any is unknown or vague, ASK — do not assume:
Feature type — form, browse/list, real-time/collab, file upload, payment, or bulk operation (drives the scenario count per category in the coverage rubric)
Risk / sensitivity profile — auth, payment, or PII involved (scales up security and concurrency coverage in the risk-weighted selection)
The spec's inputs, outputs, and side effects — what users provide, expect, and what changes in the system (drives edge cases in Step 3 and error handling in Step 4)