ARCHON SFT v2 Phase 6.5 — Readiness Validation Report
Date: 2026-06-02 Validator: Claude Sonnet 4.6 (subagent) Scope: 7 Phase 6.5 artifacts, cross-validation of 5 criteria
VERDICT: NOT READY — 3 blocking conflicts, 1 data source defect
Synthetic generation must NOT launch until conflicts C1 and C2 are resolved. Conflict C3 and defect D1 can be fixed in parallel with generation prep.
VALIDATION RESULTS
V1 — HF Search Results
Status: PASS (with noted risk)
Single usable peer-equal dataset identified: Multi-Agent-LLMs/DEBATE (apache-2.0).
7,200 usable rows across debate + relay + memory + report paradigm configs.
Peer-equal check confirmed: no supervisor/manager/orchestrator pattern in sampled rows.
Rejection of camel-ai datasets on NC licence + structural hierarchy grounds is correct.
UltraInteract_sft classification as N1-only is correct (SFT split is flat, no multi-agent turns).
Risk noted: DEBATE tasks are trivia/QA domains (manta ray biology, seating puzzles), not ARCHON-domain (network/cybersec/Etherlink). Format transfer is accepted but domain gap is real. Mitigation already documented in adversarial check section — adequate.
V2 — Synthetic Generation Plan Feasibility
Status: PARTIAL PASS — cost reasonable, hours reasonable, sample targets INCONSISTENT (see C1/C2)
Cost: $220-250 USD (generation plan estimate with prompt caching is the reliable figure; the YAML $125 figure underestimates by using a lower $/call approximation). Hours: 28-35h sequential, ~18-20h with 2 parallel workers. Feasible. Pilot gates (V1-V4) are well-designed and proportionate. Parallel launch strategy (N1+N4 terminal 1, N2 terminal 2, N3 terminal 3) is sound.
V3 — MTP Task Profiles Consistency
Status: PASS
4 new task types added correctly: family_consult [1.0, 0.65, 0.50, 0.40, 0.30] (N2 structured — moderately predictable) family_negotiate [1.0, 0.55, 0.40, 0.30, 0.20] (N3 debate — mid-predictability) family_swarm [1.0, 0.40, 0.25, 0.18, 0.12] (N4 emergent — low predictability) family_role_rotate [1.0, 0.70, 0.55, 0.45, 0.35] (meta escalation — structured)
Predictability gradient N2>N3>N4 is correct and rationale is documented.
general_conv_fr was NOT duplicated (already present). Comment confirms this.
Phase 6 submix sum assertion: 0.01+0.04+0.06+0.04 = 0.15 — PASS.
Curriculum continuity: 7 phases, steps 0-50000, no gaps, no overlaps — PASS.
DPO sub-window 42000-50000 aligned in both Python file and design doc — PASS.
Legacy multi_agent_coord/delegation_chain kept at low weight (0.8) for rehearsal — correct.
V4 — Mix Distribution Target Coherence
Status: FAIL — sample target inconsistency across three documents (see C1, C2)
V5 — METATRON / "Master" Connotation Audit
Status: CONDITIONAL PASS — one spec doc has a METATRON leak (see C3)
"master" usage in all Phase 6.5 artifacts is definitional negation only (describing what
to avoid). No content encodes master-subordinate behavior. File name
_out_synthetic_prompts_master.md is a title, not a connotation issue.
Generator script: METATRON correctly replaced by [trading-specialist] in ROSTER,
SYSTEM_BASE, and anti-pattern list. Forbidden-pattern validator checks "metatron" string.
Generation plan gate V2 checks "metatron" absence. PASS.
_out_phase_6_5_design.md line 75: schema example lists METATRON as a participant:
"participants": ["ARCHON", "<1-3 peers from NEXUS/CYPHER/AETHER/METATRON>"]
This is a design doc inconsistency — the actual generator script never uses METATRON.
Risk: low (design doc is not read by the generator), but must be corrected before sharing.
V6 — Coverage: HF + Synthetic vs Total Target
Status: FAIL — N4 coverage is severely under-specified (see C2)
CONFLICTS (blocking unless noted)
C1 — BLOCKING: N4 sample count three-way inconsistency
| Document | N4 target |
|---|---|
| _out_multi_agent_sources.yaml | 10,000 (to_generate) |
| _out_synthetic_generation_plan.md | 3,000 |
| _out_mix_distribution_target_phase65.json | 20,000 (target_samples in N4_family_swarm) |
The mix JSON is the authoritative training target: 20,000 N4 samples. The YAML says 10,000 to generate (which could mean HF covers 10K — but HF has 0 N4 rows). The generation plan says only 3,000 — this is the most severe undercount.
Resolution required: set N4 target uniformly to 10,000 across all three documents (20,000 mix target is too aggressive for entirely-synthetic N4; 10K is the YAML intent and matches the HF search gap analysis). OR keep mix at 20K and update synth plan to 20K (cost ~$200 for N4 alone via Opus templates + Sonnet expansion, per YAML estimate).
Decision needed from Jescy before launching.
C2 — BLOCKING: Aggregate N2-N4 coverage gap
Computed from authoritative sources:
| Niveau | HF available | Synth plan generates | Total | Mix JSON target |
|---|---|---|---|---|
| N2 | 2,400 | 5,000 | 7,400 | 20,000 |
| N3 | 3,600 | 7,000 | 10,600 | 30,000 |
| N4 | 0 | 3,000 | 3,000 | 20,000 |
| Total N2-N4 | 6,000 | 15,000 | 21,000 | 70,000 |
21,000 actual vs 70,000 mix target = 30% coverage. This is a 3.3× shortfall. Possible resolutions: (a) Reduce mix JSON targets to match synth capacity (N2: 7.5K, N3: 10.5K, N4: 3K or 10K). Pro: preserves current synth budget. Con: N4 remains thin. (b) Scale up synth generation to match mix targets (cost ~$800-1000 total, 3-4 days). Pro: full coverage. Con: significant cost and time increase. (c) Accept mismatch with oversampling: synth samples x10 weight to fill quota. Risk: memorisation at high oversampling factor.
C3 — NON-BLOCKING: METATRON in design doc schema
_out_phase_6_5_design.md line 75 lists METATRON as a possible participant in the
generator schema example. The generator script never actually uses METATRON (correctly
uses [trading-specialist]). Fix: replace METATRON with [trading-specialist] in the
schema example. One-line edit, no functional impact.
DEFECTS (non-blocking but must fix before mix build)
D1 — UltraInteract_sft N2 filter is broken
Mix JSON entry for N2_family_consult uses UltraInteract_sft with filter
trajectory_length >= 4. The HF search report (section 2) explicitly confirms:
"The parent_id tree is the preference learning split (_pair), NOT this SFT split."
The SFT split is flat (instruction, response) pairs — no trajectory_length field exists.
This filter will either fail at runtime or return 0 rows.
Impact: 8,000 planned N2 samples from this source will be unavailable. Mitigation: remove UltraInteract N2-filtered source from N2 mix entry. Replace with additional synth generation (+3,000 N2) or oversample DEBATE relay/report configs. Net effect on C2 gap: worsens N2 shortfall by 8K additional samples.
SUMMARY TABLE
| Check | Status | Action |
|---|---|---|
| HF peer-equal datasets identified | PASS | None |
| Synthetic cost feasible | PASS | Use $220-250 budget |
| Synthetic hours feasible | PASS | 28-35h sequential |
| MTP profiles consistent | PASS | None |
| Phase 6 submix sum = 15% | PASS | None |
| Curriculum continuity 0-50K | PASS | None |
| DPO sub-window alignment | PASS | None |
| N4 sample count aligned | FAIL — C1 | Resolve before launch |
| N2-N4 coverage vs mix targets | FAIL — C2 | Resolve before launch |
| METATRON absent in generated content | PASS | None |
| METATRON in design doc schema | WARN — C3 | One-line fix |
| UltraInteract N2 filter valid | FAIL — D1 | Remove/replace before mix build |
| DPO egalitarian dependency order | PASS | None |
TOTAL COST ESTIMATE (Phase 6.5 complete)
Scenario A — current synth plan (17K samples): Synthetic generation: $220-250 GPU cost Phase 6 (8K steps, RTX PRO 6000 ~$1.2/hr, ~8-10h): $10-12 Total Phase 6.5: ~$230-262
Scenario B — scaled to match mix targets (~54K N2-N4 samples): Synthetic generation: ~$800-1000 GPU Phase 6: ~$10-12 Total Phase 6.5: ~$810-1012
Recommended: resolve C1/C2 first, then choose scenario.
PRE-LAUNCH CHECKLIST
Before running python _out_synthetic_generator.py:
- C1 resolved: N4 target aligned across all three documents
- C2 resolved: synth targets or mix JSON targets reconciled
- C3 fixed: METATRON replaced by [trading-specialist] in _out_phase_6_5_design.md line 75
- D1 acknowledged: UltraInteract N2 source removed from mix JSON or filter corrected
- Dry-run passes:
python _out_synthetic_generator.py --niveau all --dry-run - Pilot 50 samples N2 inspected manually before full run
- ANTHROPIC_API_KEY set in environment
- synthetic_out/ and logs/ directories created