pantheon-ai/acceptance-criteria
Write clear, testable acceptance criteria for user stories and feature delivery; use when defining done conditions, creating measurable requirements, applying INVEST checks, documenting negative scenarios, and aligning product, engineering, and QA on expected outcomes.
Does it follow best practices?
Evaluation — 91%
↑ 1.17xAgent success when using this tile
Validation for skill structure
Evaluation results
84%
11%E-commerce Checkout Implementation
Checkout Flow Workflow
Given/When/Then format
73%
53%
Measurable timing
100%
100%
Observable outcomes
70%
80%
Negative scenarios
100%
100%
Single action When
80%
80%
Essential Given setup
70%
100%
User behavior scenarios
20%
60%
Out of scope section
100%
100%
Checkbox format
0%
100%
User outcome focus
60%
80%
Without context: $0.2173 · 1m 13s · 9 turns · 10 in / 3,095 out tokens
With context: $0.5753 · 2m 46s · 29 turns · 586 in / 6,342 out tokens
98%
25%User Registration System
API Rule Validation
Rule-oriented format
60%
100%
Specific response codes
100%
100%
Form validation rules
100%
100%
Error handling details
92%
100%
Checkbox format usage
0%
100%
Negative scenarios
100%
100%
Measurable constraints
90%
100%
Independent requirements
75%
100%
User outcome focus
80%
100%
Stakeholder alignment
0%
60%
Scope boundaries
0%
100%
Without context: $0.2059 · 58s · 9 turns · 58 in / 3,057 out tokens
With context: $0.3451 · 1m 22s · 16 turns · 1,051 in / 3,700 out tokens
94%
13%Analytics Dashboard Performance
Performance Measurements
Specific timing requirements
100%
100%
Measurable quantities
100%
100%
Observable UI behavior
93%
93%
Rule-oriented format
50%
90%
Negative performance cases
100%
100%
Avoids vague terms
60%
70%
User outcome focus
88%
88%
Checkbox validation format
0%
100%
Multiple measurement types
100%
100%
Scope definition
50%
100%
Without context: $0.2162 · 1m 42s · 10 turns · 10 in / 2,959 out tokens
With context: $0.3154 · 1m 26s · 17 turns · 1,363 in / 3,626 out tokens
88%
-2%User Onboarding Experience
INVEST Criteria Validation
INVEST validation applied
100%
100%
Given/When/Then sequences
100%
60%
Stakeholder alignment mention
100%
100%
Sequential step validation
80%
70%
Testable binary criteria
90%
90%
User behavior scenarios
63%
75%
Business value emphasis
100%
100%
Estimable clarity
88%
100%
Single iteration scope
50%
100%
Implementation flexibility
100%
100%
Without context: $0.2812 · 2m 3s · 10 turns · 59 in / 4,984 out tokens
With context: $0.4163 · 2m 32s · 18 turns · 338 in / 5,647 out tokens
92%
18%Product Search Enhancement
Search Edge Cases
Rule-oriented format
83%
75%
Comprehensive edge cases
87%
93%
Input validation rules
92%
83%
Measurable result limits
33%
92%
Performance timing
100%
100%
Error handling scenarios
90%
100%
Result formatting rules
80%
100%
Checkbox validation format
0%
100%
Independent requirements
83%
83%
User outcome focus
67%
100%
Without context: $0.2424 · 1m 39s · 10 turns · 59 in / 3,764 out tokens
With context: $0.4390 · 2m 23s · 23 turns · 18 in / 5,313 out tokens
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