Artifex/docs/handoff_current_state_20260817.md

Artifex Handoff - Current State - 2026-08-17

Current Objective

We have been repairing and dogfooding the CRYPTO / PROTOCOL VENTURE COHORT pipeline, specifically the V0.3.1 cohort and the V0.3.2B token-judge evidence repair.

Hard constraint: NO NEW IDEAS for the repair work. Only reprocess the existing six former V0.3.1 survivors.

Safety constraints remain active:

• Do not issue or sell native tokens.
• Do not sell NFTs or memberships.
• Do not launch mainnet.
• Do not create liquidity or market make.
• Do not contact investors, users, or customers.
• Do not fundraise.
• Do not spend real money.

Environment

• Workspace: S:\PycharmProjects\Artifex
• Repo remote: http://192.168.1.162:3000/daniel/Artifex.git
• Database: sqlite:///db.sqlite3
• SearXNG: http://192.168.1.162:8080
• Qwen: http://192.168.1.162:8002
• Current date in environment: 2026-08-17
• Known harmless push warning: git: 'credential-manager-core' is not a git command. See 'git --help'.

Spark remote validation was previously blocked by SSH auth:

• daniel@192.168.1.162: Permission denied (publickey,password).

Current Cohort

• Cohort ID: CPV031-20260816215626-66d636b2
• GraphRun: 10
• Existing six former V0.3.1 survivors only:
  • Agent Passport Clearinghouse
  • PatchBond Network
  • ProofGrid Compute Attestation Network
  • ProofBond
  • Compute Clearance Network
  • ProofGrid Compute Escrow

Latest Implemented Work

V0.3.2B Token Judge Evidence Repair

Implemented strict Sol Token Utility Judge evidence validation.

Required non-empty fields now enforced:

• argument_for_native_token
• argument_against_native_token
• external_collateral_counterfactual
• native_token_removed_breaks
• native_token_removed_explanation
• material_improvements_over_USDC_ETH
• native_asset_costs_and_risks
• final_rationale

Behavior now:

• Rejects incomplete Sol judge response.
• Retries incomplete judge response up to 3 attempts.
• Raises ValueError after exhausted retries.
• Does not fall back to deterministic/heuristic classification when Sol produced an incomplete response.
• Normalizes Sol response when external_collateral_counterfactual appears nested under counterfactual_analysis.
• Uppercases utility_scores keys during normalization.
• Persists final_rationale in token metadata as well as TokenUtilityAssessment.rationale.
• crypto_score_row() now reuses persisted token_utility_assessment instead of calling the token judge again.
• Final Sol IC prompt was compacted so it returns usable JSON.

Rationale invariants now checked:

• Every TOKEN_OPTIONAL rationale must explain why ETH/USDC/external collateral is preferable despite claimed degradation.
• Every TOKEN_ESSENTIAL / TOKEN_STRONGLY_JUSTIFIED rationale must explain what protocol-specific property cannot be reproduced economically enough with ETH/USDC/external collateral.
• The code does not automatically promote due to material degradation.

Latest Six-Proposal Results

Before/after classifications from V0.3.2B:

Company	Before	After	Score	Final IC Decision	Final IC Score	Required Field Gaps
Agent Passport Clearinghouse	TOKEN_OPTIONAL	TOKEN_UNNECESSARY	18.0	REJECT_TOKEN_NOT_NEEDED	62.3	[]
PatchBond Network	TOKEN_OPTIONAL	TOKEN_OPTIONAL	48.0	REJECT_TOKEN_NOT_NEEDED	66.4	[]
ProofGrid Compute Attestation Network	TOKEN_OPTIONAL	TOKEN_OPTIONAL	42.0	REJECT_TOKEN_UTILITY_WEAK	63.6	[]
ProofBond	TOKEN_OPTIONAL	TOKEN_OPTIONAL	54.0	REJECT_TOKEN_UTILITY_WEAK	64.3	[]
Compute Clearance Network	TOKEN_OPTIONAL	TOKEN_STRONGLY_JUSTIFIED	78.0	PROTOCOL_VALIDATE	79.7	[]
ProofGrid Compute Escrow	TOKEN_OPTIONAL	TOKEN_OPTIONAL	58.0	REVISE_TOKEN_MODEL	67.9	[]

Current corrected cohort state:

• Token unnecessary: 1
• Token optional/routed SaaS: 4
• Token strongly justified: 1
• Token essential: 0
• Serious crypto survivors: 0
• Crypto survivors: 0
• Autonomous crypto survivors: 0
• Assisted high-potential: 0
• Finalists: 0
• V0.3.2B required field gaps: 0
• Token red-team failures:
  • TOKEN_NOT_REQUIRED: 5
  • YIELD_DEPENDENCY: 1
  • SLASHING_DEPENDS_ON_HUMAN_JUDGMENT: 1

Important nuance: Compute Clearance Network became TOKEN_STRONGLY_JUSTIFIED, but final cohort finalists remain 0. It is not automatically promoted to finalist.

Latest Files Changed

• agents/crypto_venture.py
  • Strict token judge evidence validation/retry/fail-closed behavior.
  • Token judge response normalization.
  • Persisted required fields.
  • Reused persisted token assessment in crypto_score_row().
  • Compact final Sol IC prompt.
• tests/test_crypto_venture_cohort.py
  • Added coverage for complete required judge fields.
  • Added retry-success and retry-exhaustion/fail-closed tests.
• control_plane/ventures/management/commands/export_crypto_venture_cohort.py
  • Added V0.3.2B Before/After markdown section.
• docs/crypto_venture_cohort_v031_20260816.md
  • Updated exported V0.3.2B report.
• docs/crypto_venture_cohort_v031_20260816.json
  • Updated exported V0.3.2B report data.

Latest Commits Pushed

Recent relevant commits:

• 35d3346 Repair crypto token judge evidence export
• 6e89ea8 Require complete crypto token judge evidence
• 052d1fc Add corrected crypto cohort V0.3.1 export
• 94b9ab6 Repair crypto token utility scoring
• 54ffe92 Add crypto protocol cohort V0.3.1 export

The most recent push succeeded to main with the known harmless credential-manager warning.

Verification

Latest verification passed:

• python manage.py check: passed
• python -m pytest -p no:django -q tests/test_crypto_venture_cohort.py: 14 passed
• Full suite: 157 passed, 1 skipped

Warnings are existing Python/Django/LangGraph deprecation warnings and pytest collection warnings for TestRun; no failing tests.

Current Git State At Time Of Handoff

After the latest commit/push, git status --short was clean.

This handoff file itself is newly added after that push and should be committed/pushed if the user wants the note persisted remotely.

If Continuing

Recommended next steps only if the user asks to continue:

1. Commit and push this handoff note if desired.
2. If further V0.3.2B analysis is requested, inspect docs/crypto_venture_cohort_v031_20260816.md first.
3. Do not regenerate ideas unless explicitly instructed.
4. Do not rerun broad research unless explicitly requested or needed for a new judge repair.
5. Keep all token/mainnet/fundraising/user-contact/no-spend stop conditions active.

Model Studio V0.1 Update

Commit d61751a Add Guard model studio foundation added the initial Model Studio domain.

Key files:

• control_plane/model_studio/models.py
  • Canonical Django state for training projects, immutable dataset versions and recipes, checkpoints, experiments, runs, evaluation suites/runs/results, regression-bank items, failure clusters, promotion policies/decisions, overnight programs, reports, and artifacts.
• control_plane/model_studio/services.py
  • Guard import/archaeology, dataset curation, benchmark gate, experiment contract and fingerprinting, simulated run/promotion logic, deadline reserve checks, and morning report.
• control_plane/model_studio/profiles.py
  • GuardModelProfile, based on the discovered ForgeGuard layout.
• control_plane/model_studio/backends.py
  • FakeTrainingBackend for tests and SparkGuardBackend for profile-generated remote commands only.
• Commands:
  • python manage.py modelstudio_import_guard --repository <local ForgeGuard path> --slug guard-3b
  • python manage.py modelstudio_dataset_audit --project guard-3b
  • python manage.py modelstudio_overnight --project guard-3b --dry-run
• Minimal UI:
  • /model-studio/

Guard was imported locally for archaeology from:

• S:\PycharmProjects\Me3\tools\ForgeGuard

Current Guard project state in Artifex DB:

• Training project slug: guard-3b
• Current base-model Champion candidate: Qwen/Qwen2.5-Coder-3B-Instruct
• Selection: explicitly human-mandated starting Champion
• Evidence status: PENDING_FRESH_SPARK_BASELINE
• Training project status: NEEDS_REPAIR
• Benchmark integrity: WARNING, not valid
• Spark checkout is not registered or verified
• Fresh baseline is missing

No local Guard training/evaluation was run. The local machine is unsuitable and the user explicitly required Spark-only execution.

Spark connectivity is confirmed (ssh spark hostname returned Inceptal), but read-only inspection found no ForgeGuard directory under /workspace, /home, or /opt. Do not run training until a Spark ForgeGuard checkout path is provided or explicitly synced, then register it with --spark-working-directory and verify it.

Dataset curation result:

• 79 imported JSON artifacts
• 49 blocked
• 30 warning-only
• 0 approved training datasets
• Decision: NO_TRAINING_DATASET_APPROVED

Important curation facts:

• Summary JSON files are non-training artifacts.
• Candidate/provisional corpora are blocked.
• full_source_c4_guard_candidate_v12 is explicitly candidate-only and has not been trained.
• The Qwen 3B verified pilot has 88 records and a claimed EVMBench exclusion, but stays WARNING pending record-level provenance/schema/coverage and contamination verification.
• No Spark baseline/canary/overnight program is permitted yet.

Latest verification after Model Studio work:

• python manage.py check: passed
• python -m pytest -p no:django -q tests/test_model_studio_v01.py: 6 passed
• Full suite: 163 passed, 1 skipped

Guard Dataset Factory Update

Commit e27df77 Add Guard dataset curation pipeline added Spark-backed dataset curation.

The source policy is now:

• All existing Guard data, including legacy holdouts, is authorized as a curation source by user mandate.
• Former holdouts can enter a new training version only after source-hash re-splitting produces new validation and regression manifests.
• Existing benchmark suites must be replaced/versioned before comparisons if their old holdout sources are used for training.
• Source data is never overwritten; every output is a new immutable DatasetVersion.

Spark Guard location:

• /home/daniel/forgeguard
• Active data root inspected: /home/daniel/forgeguard/project/data

The first bad recursive Spark inventory created 227,137 null-record-count DB rows from individual evidence JSON objects. Those malformed local DB rows were purged. The importer now accepts only explicit manifest paths; it does not recurse through evidence stores.

Qwen Dataset Curator proposal:

• Proposal ID: 0afcb3f5-a097-4461-b890-14d350e9d8f6
• Qwen identified heterogeneous schemas, weak/contradictory labels, provenance risks, and exact-holdout handling requirements.
• Its proposal is persisted as DatasetCurationProposal and a Model Studio artifact.

Spark materialized versions:

1. guard_curated_v01

   • /home/daniel/forgeguard/artifex_dataset_versions/guard_curated_v01/
   • Train 4,684; validation 657; regression 541.

2. guard_curated_v02 (current recommended corpus)

   • Train manifest: /home/daniel/forgeguard/artifex_dataset_versions/guard_curated_v02/train.json
   • Validation manifest: /home/daniel/forgeguard/artifex_dataset_versions/guard_curated_v02/validation.json
   • Regression manifest: /home/daniel/forgeguard/artifex_dataset_versions/guard_curated_v02/regression.json
   • Artifex DatasetVersion ID: 416fc9dd-c922-4581-8ed5-ca10a488d224
   • Train: 3,030
   • Validation: 437
   • Regression: 332
   • Train SHA-256: d4c1a6accee0fac511641a24287cfdb469819fdd6d34af720c7349dc66b4803c
   • Validation SHA-256: 3e3d5ad0d306bdd4a530fd2cf1d32bea030980af8d964d95c34b28237f6d5f
   • Regression SHA-256: a868c4221f291953a91cf5e03f8163b2fa4e134db5f21e369fbf7c75c2387f1c
   • Source records read: 10,057
   • Accepted after strict repair: 3,799
   • Exact duplicates removed: 4,099
   • Malformed/weak-schema records removed: 2,159
   • Strict repair requires Solidity pragma, parseable JSON output with findings, and excludes c4_invalid records.

No Guard model training was started. The next required milestone is to deploy/sync Artifex state to Spark, register a new evaluation suite version using the v02 validation/regression manifests, run the fresh base-model baseline on Spark, then create the first actual training canary.