Fid Ttur Recovery Protocol

---
name: fid_ttur_recovery_protocol
description: Assemble a bounded soft-mode recovery protocol that exercises FID statistics, FID distance, and TTUR update skills.
---

# Fid Ttur Recovery Protocol

Use this skill when a recovery or implementation needs the `recovery_protocol` module from the TTUR/FID paper without rereading the original repository. Do not use it to claim full GAN reproduction unless real image features, dataset statistics, and training evidence are available.

## Inputs
- Numeric arrays or JSON files matching the module contract.
- For recovery orchestration, a module-plan target and runtime handoff.

## Outputs
- Deterministic JSON-compatible statistics, distances, traces, or recovery checks.
- Diagnostics sufficient to audit reduced/proxy recovery.

## Workflow
1. Validate input shapes and finite numeric values.
2. Execute the module-specific deterministic script in `scripts/`.
3. Preserve diagnostics and command evidence when used in recovery.
4. Treat synthetic activations or toy dynamics as proxy evidence only.

## Validation
Run `python tests/test_fid_ttur_recovery_protocol.py` from this skill directory.

## Limitations
This skill is self-contained and does not require the original TTUR repository. It does not download Inception models or train full GANs.

## Refinement Note
Recovery users should record both descriptive `evidence_type` and validator-compatible `kind`/`evidence` fields in generated skill invocation logs.