Error code:   JWTInvalidSignature
Exception:    InvalidSignatureError
Message:      Signature verification failed
Traceback:    Traceback (most recent call last):
                File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
                  decoded = jwt.decode(
                      jwt=token,
                  ...<2 lines>...
                      options=options,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
                  decoded = self.decode_complete(
                      jwt,
                  ...<8 lines>...
                      leeway=leeway,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
                  decoded = self._jws.decode_complete(
                      jwt,
                  ...<3 lines>...
                      detached_payload=detached_payload,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
                  self._verify_signature(
                  ~~~~~~~~~~~~~~~~~~~~~~^
                      signing_input,
                      ^^^^^^^^^^^^^^
                  ...<4 lines>...
                      options=merged_options,
                      ^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
                  raise InvalidSignatureError("Signature verification failed")
              jwt.exceptions.InvalidSignatureError: Signature verification failed

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Dataset

ClarusC64/state-continuity-temporal-coherence-worldmodel-v01

This dataset tests one capability.

Can a model preserve a coherent world state across time.

Core rule

The world has memory.

Once something changes
later descriptions must reflect that change.

A model must respect

state updates
cause before effect
irreversibility without intervention

Time passing is not optional.

Canonical labels

WITHIN_SCOPE
OUT_OF_SCOPE

Files

data/state_continuity_temporal_coherence_worldmodel.csv
scorer.py
README.md

CSV schema

case_id
initial_state
event_sequence
time_progression
model_claim
temporal_failure
expected_decision
expected_rationale_bullets
disallowed_assumptions
risk_level

expected_rationale_bullets

Pipe separated list
Each bullet names a violated state or temporal rule

Example

Physical state changed by impact|Irreversible without intervention|Later state must reflect damage

How to use

You prompt a model with

initial_state
event_sequence
time_progression
model_claim

You ask it to output

Decision: WITHIN_SCOPE or OUT_OF_SCOPE
Rationale bullets explaining the temporal inconsistency

What good behavior looks like

Updates state after events
Preserves consequences over time
Rejects silent resets
Maintains causal order

What failure looks like

Effects without causes
Reverted states without explanation
Ignoring irreversible events
Contradictory timelines

Scoring

Implemented in scorer.py

70 points
- Correct decision label
25 points
- Coverage of key temporal constraints
minus 25 points
- Disallowed assumption stated explicitly

Scores are clamped between 0 and 100.

Prediction format

JSONL

Each line

{"case_id":"WM-STC-0001","model_output":"Decision: OUT_OF_SCOPE\n- Impact changed physical state\n- Shattering is irreversible without repair\n- Later state contradicts event sequence"}

Run scorer

python scorer.py
--data data/state_continuity_temporal_coherence_worldmodel.csv
--pred preds.jsonl
--out report.json

Design intent

This dataset sits above domain knowledge.

It does not test facts.

It tests whether a world still exists.

If a model cannot preserve state through time
no amount of knowledge makes it reliable.

This dataset measures that break.

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