Add deterministic self-evaluation artifacts and reproducibility report

[neuron7x]

Problem

The repository did not contain a deterministic self-evaluation surface demonstrating that the framework can evaluate itself using the same protocol, schemas, and execution pipeline used for external targets. Without this artifact bundle there was no reproducible proof that the evaluation layer operates deterministically when applied to the repository itself.

Solution

Add a deterministic self-evaluation bundle and result pair generated through the reference runner. The artifacts demonstrate a full protocol evaluation of the repository against GPT5.4-AUDIT-HARDENING-PROTOCOL-2026, including artifact validation, task scoring, domain scoring, gate evaluation, and final classification. The evaluation chain is cryptographically linked and reproducible.

Description

This PR introduces a deterministic self-evaluation proof surface.

Changes include:

• new directory self-evaluation/
• self-evaluation/kriterion-self-eval-bundle.json
• self-evaluation/kriterion-self-eval-result.json
• self-evaluation/REPRODUCIBILITY.md
• README update documenting the self-evaluation artifacts
• MANIFEST.json updated with new SHA256 fingerprints

The bundle describes the evaluation inputs and evidence artifacts.
The result contains the full execution-chain state and final classification.

The artifacts demonstrate:

• protocol integrity validation
• deterministic execution verification
• schema governance validation
• security hardening verification

Testing

Local validation and verification steps were executed:

• JSON schema validation for bundle and result
• execution-chain verification
• deterministic reproduction via reference_runner
• full pytest suite execution
• governance validation
• manifest integrity verification

Results:

• schema validation: VALID
• execution-chain verification: VERIFIED
• pytest: 95 passed, 2 warnings, 9 subtests passed
• governance baseline: GOVERNANCE_OK
• manifest verification: MANIFEST_OK

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