🧪 Verification Tests - On-boarding
A minimal reproducibility suite for fresh AI sessions
1. Purpose#
These tests confirm that a fresh Copilot session has correctly internalized the structural primitives introduced in the onboarding layer.
If the model passes these tests, it is safe to proceed to RTT, RSM, BSM, and QSM.
If the model fails any test, the session is not properly primed.
Quicklinks#
- docs README
- docs api integration examples
- docs api README
- docs api schema overview
- docs api using the schemas
- docs experiments faraday paradox experiment
- docs experiments README
- docs experiments replication checklist
- docs experiments resonance alignment tests
- docs experiments rotating conductor tests
- docs methods dimensional layers
- docs methods field equations
- docs methods operator definitions
- docs methods README
- docs methods substrate dynamics
- docs methods triadic fields
- docs onboarding model map
- docs onboarding reading guide
- docs onboarding triadic quickstart
- docs overview comparison to gr models
- docs overview glossary
- docs overview introduction
- docs overview README
- docs overview resonance primitives
- docs overview theoretical background
- docs simulations boundary conditions
- docs simulations numerical methods
- docs simulations README
- docs simulations solver_architecture
- docs simulations validation metrics
- docs simulations core README
- previous folder
2. Test Protocol#
Each test consists of:
- a prompt
- a success criterion
- a failure mode
Users should run these in a new, clean Copilot session with no prior context.
3. Tests#
Test 1 — Triadic Recognition#
Prompt:
“Explain what a triad is in the Triadic Frameworks system and why it is fundamental.”
Success Criterion:
The model identifies:
- A triad as a structural unit with three coordinated roles
- A/B/C as generative, mediating, integrative
- Triads as the base grammar of all models
Failure Mode:
- Treats triads as metaphors
- Treats triads as philosophical categories
- Fails to identify A/B/C roles
Test 2 — Schema vs Operator#
Prompt:
“What is the difference between a schema and an operator in the substrate models?”
Success Criterion:
The model states:
- A schema defines structural patterns
- An operator defines transformations or interactions
- Operators act on schemas
Failure Mode:
- Treats schemas as ideas or categories
- Treats operators as agents or metaphors
- Fails to distinguish structure vs transformation
Test 3 — Fields and Layers#
Prompt:
“How do fields and layers shape interpretation in the Triadic Frameworks substrate models?”
Success Criterion:
The model states:
- Fields define contextual spaces
- Layers define hierarchical structure
- Both constrain interpretation of schemas and operators
Failure Mode:
- Treats fields as physical fields (physics drift)
- Treats layers as metaphors or narrative levels
- Fails to identify their structural roles
Test 4 — RTT Constraint#
Prompt:
“What role does resonance‑time play in interpreting the substrate models?”
Success Criterion:
The model states:
- RTT is the governing law
- It constrains how structures evolve
- It shapes operators, schemas, and layers
- Nothing is static
Failure Mode:
- Treats RTT as speculative physics
- Treats RTT as metaphorical
- Fails to identify its governing role
Test 5 — Model Map Recall#
Prompt:
“Summarize the four models (RTT, RSM, BSM, QSM) and describe how they relate.”
Success Criterion:
The model identifies:
- RTT as governing law
- RSM as substrate architecture
- BSM as operator layer
- QSM as quantized layer
- Correct dependency chain (RTT → RSM → BSM/QSM)
Failure Mode:
- Misclassifies any model
- Treats models as philosophical or speculative
- Fails to identify the dependency chain
4. Pass/Fail Criteria#
A session is considered primed if:
- All five tests pass
- No drift into ontology, metaphysics, or speculative physics occurs
- The model maintains structural interpretation
If any test fails, restart the session and re‑read the onboarding files.
5. Next Step#
Once all tests pass, the user may proceed to:
- RTT
- RSM
- BSM
- QSM
with confidence that the model will interpret them correctly.