Graph data fabric - semantic graph, hybrid persistence
- Panel date
- Pending
- Confidence
- —
- Satisfied
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- Architecture
- GVAR v3.3 - pending first run via webhook
Evidence ledger · public receipt inventory
Receipts keep the Determinism Ladder honest. Each item names the trade, the artifact, the current checks, and the next proof needed.
The page is a public ledger, not a victory lap. It shows what shipped, what is partial, and where the evidence chain still needs another turn.
Receipts
Linked public items
Repository plans
Sanitized public panel record
The site does not publish raw model votes or private run internals. It does publish the public shape of a run: status, panel date, confidence, satisfied count, architecture, and the article it judged.
Verified
Advisory
Pending
Initial public primer drafted from primary papers and public model-building concepts. Needs GVAR panel pass before promotion to verified status.
Initial public primer drafted for the StoneyTECH MCP page. Needs GVAR panel pass before promotion to verified status.
Panel-verified clean under GVAR v3.3 execution 8003 on 2026-05-03 — 5 of 6 verifiers satisfied at average confidence 0.98, ZERO critical findings, 1 IMPORTANT (Security; same primer-register trade pattern as piece #1), 3 nice-to-haves. Cross-piece calibration data (Demystify #1 vs #2): IDENTICAL convergence pattern — both pieces 5/6 satisfied, 0 critical, 1 Security IMPORTANT, panel confidence 0.98, all cross-family voice verifiers >=0.97. The Security lens consistently finds "primer touches a security topic at audience depth without naming the threat at architect depth" — which is by design (the cross-link to the architect-register treatment is the deliberate handling). Architecture lens consistently finds "could extend into deployment-context territory" — also by design. The voice template is stable across two iterations. The panel response is predictable. The Demystify register can be wired into learning-agent (register=primer mode) with high confidence that generated drafts will pass the panel on first run with the same convergence pattern. Second piece of the Demystify AI series. Audience: technical generalists (IT, security, ops, project managers, anyone using AI tools daily but never given a working mental model).
Panel-verified clean under GVAR v3.3 execution 7841 on 2026-05-03 — 5 of 6 verifiers satisfied at average confidence 0.98, ZERO critical findings. Calibration data for the rest of the Demystify AI series: cross-family voice verifiers all converged at >=0.97. Primer-register voice holds against the same gold-standard signal as architect-register. Security/Architecture lenses carry less load in a primer (no architectural decisions to threat-model), but still surface real gaps when an audience anecdote touches a known attack surface. The convergence rule handles primer pieces cleanly without re-tuning. First piece of the Demystify AI series. Audience: technical generalists — IT coworkers, sysadmins, helpdesk leads, project managers, security analysts who use AI tools daily but lack a working mental model for the mechanism under the hood. Voice: pragmatic, friendly, anti-hype. Structure: give an almost-correct metaphor, refine it just enough for use, then show why the imperfection creates the value.
Panel-verified clean under GVAR v3.3 (6-verifier panel + Path A purity) execution 2748 on 2026-04-29 — 5 of 6 verifiers satisfied at average confidence 0.98, ZERO critical findings, 1 IMPORTANT (Security lens on prompt-caching threat surface; recorded above for follow-up). Architecture lens summary: "fully centers deployment context as decision-zero and does not treat cloud-managed APIs as the universal architectural default. It explicitly distinguishes public cloud, sovereign/private cloud, restricted-network, and true air-gap architectures across models, APIs, RAG, agents." Sister piece to GVAR-36 (threat-surface-layer-by-layer); together they close the v3.2 panel's two gap classes (axioms #17 and #18) at the depth the panel asked for. 104-second panel run on the Path A self-verify path. Per the convergence rule (≥4/6 satisfied + no criticals), the Security IMPORTANT does not block panel-verified status; it is recorded as outstanding refinement for a future pass.
Panel-verified clean under GVAR v3.3 (6-verifier panel + Path A purity) execution 2746 on 2026-04-29 — 6 of 6 verifiers satisfied at average confidence 0.99, ZERO critical findings, ZERO importants, 2 nice-to-have refinements (recorded above for a future pass). Security lens: "fully satisfies the Axiom #17 threat-surface lens. It names adversarial-input paths, prompt injection vectors, supply-chain assumptions, credential/token disclosure risks, data exfiltration paths, confused-deputy risks, memory poisoning, tool-output injection." Architecture lens: "satisfies the deployment-context-first requirement. It does not treat cloud-managed APIs as universal defaults." Structure pre-reviewed with GPT-5.5-pro via Oracle MCP (verdict: Approach A — seven sub-sections per lever, 4-part rhythm). 41-second panel run (Path A self-verify path).
Panel-verified under GVAR v3.2 (6-verifier panel) execution 2500 on 2026-04-28. Convergence rule satisfied: 5 of 6 verifiers satisfied at confidence ≥ 0.95, zero critical findings. The Security lens returned needs_changes with one IMPORTANT (not critical) finding — §2 (Single REST endpoint via plain function calling) inherits the same threat-model coverage gap that the original Cheaper-alternatives section closed for shell + CLI; the augmentation didn't extend the threat-model section to also cover the REST path. Recorded in outstanding_refinements; addressed in a follow-up pass (per the convergence rule, important-only findings don't block panel-verified status, but they're permanent record). Architecture lens satisfied cleanly with one nice-to-have (REST placement still depends on residency/regulatory context). Panel confidence 0.98.
Panel-verified clean under GVAR v3.3 (6-verifier panel + Path A purity) execution 2719 on 2026-04-29. 6 of 6 verifiers satisfied at confidence >= 0.95, ZERO critical findings, zero importants. Average panel confidence 0.99. Both domain-specialized lenses (Security, Architecture) returned clean satisfied verdicts: Security at 0.99 with 0 critiques ("the article matches the gold standard and closes the prior security-lens gaps. It now names the threat surface for every lever, adds a matrix Threat-surface column, covers prompt injection, credential exposure, supply-chain risk, confused-deputy paths, excessive agency, memory poisoning, and deployment-context"); Architecture at 0.99 with 0 critiques ("the article now satisfies axiom #18: deployment context is explicitly chosen before model selection, and the decision tree correctly treats cloud, sovereign/private cloud, and on-prem/ air-gap as first-order architectural constraints"). The 16 critiques v3.2 surfaced on run 2201 are ALL closed. GVAR v3.3 architecture introduced 2026-04-29: a Self-Verify Check ifElse node after Fetch Gold Standard routes self-verify (target_path == gold_standard_path) directly to a Synthesize Self-Verify Inputs Code node that produces the same JSON shape as Parse Generator Output, then converges with the non-self- verify branch at Build Verifier Prompt. The Generator is no longer called in self-verify mode. Run time dropped from 7+ min (with frequent Anthropic API timeouts) to 60 seconds. The path here was: v3.2 run 2201 surfaced 16 critiques; commit 28c1248 augmented the article to close them; v3.2 run 2499 confirmed 15 closed but caught one residual CRITICAL at the MCP "Cheaper alternatives first" inline callout; commit 28c1248 added the inline caveat; three subsequent re-runs (2601, 2607, 2617) blocked by Generator API timeouts; GVAR-38 workflow patch bypassed Generator entirely in self-verify; v3.3 run 2719 converged 6/6 clean. The verification chain doing exactly what it exists for, end-to-end.
Panel-verified clean under GVAR v3.2 (6-verifier panel) execution 2501 on 2026-04-28. 6 of 6 verifiers satisfied at confidence ≥ 0.95, ZERO critiques across all severities. The augmented essay (PII/PHI surface in the trace store, placement-by-classification table with self-host alternatives, "Threat model for LLM-as-judge" section 4a) closed both domain-specialized lenses on the first re-run. Security-lens summary: "It names the trace store as a PII/PHI and credential-adjacent exfiltration surface, addresses deployment context and data residency." Architecture-lens summary: "It explicitly rejects cloud-managed observability as the universal default, ties trace placement to data classification and residency obligations." Panel confidence 0.99.
Panel-verified under GVAR v3.2 (6-verifier panel) execution 2502 on 2026-04-28. Convergence rule satisfied: 5 of 6 verifiers satisfied at confidence ≥ 0.95, zero critical findings. The Security lens returned needs_changes with one IMPORTANT finding flagging that the OWASP LLM Top 10 (2025) numbering in the new threat-model section may not match the current OWASP registry — recorded in outstanding_refinements; verify and refine in a follow-up pass. Architecture lens satisfied cleanly. Cross-family verifiers all satisfied; their nice-to-haves (zero-latency phrasing, 17× cost framing, chunk-size measurement, injection-strip caveat) are pre-existing refinements carried in outstanding_refinements. Panel confidence 0.98.
Panel-verified under GVAR v3.2 (6-verifier panel) execution 2503 on 2026-04-28. Convergence rule satisfied: 5 of 6 verifiers satisfied at confidence ≥ 0.95, zero critical findings. The Security lens returned needs_changes with one IMPORTANT finding — the latency-critical workaround "tiered system where a fast small model handles 90% of queries and only escalates to a frontier model on the long tail" doesn't name the data-exfiltration / classification- leak surface at the escalation boundary. Recorded in outstanding_refinements; addressed in a follow-up pass. Architecture lens summary: "It explicitly makes deployment context the first architectural decision when residency, latency, air-gap, regulatory, benchmark, or specialization constraints bind." Cross-family verifiers all satisfied at high confidence — Gemini and Grok perfect on the byte-identical augmented article. Panel confidence 0.98. History note (preserved from prior cycle): the v3.1A run executed 1787 only after the panel caught a critical bug in execution 1783 — the frontmatter axiom_outcomes[12].note had listed five exceptions that did not match the body's actual five sections. Fix in commit 6794f39, re-ran, panel converged 4/4. The verification chain doing exactly what it exists for; v3.2 confirmed it on the augmented artifact 2026-04-28 at 5/6.
Shipped
The style gate rejects first-person framing, second-person address, weak connector prose, passive drift, and employer-implied narration across published articles and public contract strings.
The identity gate keeps the site framed as anonymous learning synthesis, public-source study, and reference build notes with no employer representation or originality claim.
The generator exports published pages, articles, axioms, builds, ladder placements, applied evidence, and proof receipts from one static contract.
The site now exports a public graph linking pages, articles, axioms, builds, repositories, proof receipts, and the public MCP surface itself.
The axioms page now names how StoneyTECH judges its own implementation: what holds, what is partial, and what proof still has to close.
The build refuses article publication without a verification status matching the local verification log contract.
The axiom catalog gives recurring engineering judgment stable names, tiers, citations, and applied-evidence counts.
Reusable sidecars keep loaded terms short in prose while giving human and agent readers enough local context.
The companion article maps AI stack levers to threat surfaces, citations, and mitigations before higher agency enters the design.
The deployment-context article places cloud, sovereign cloud, private cloud, and air-gap constraints before model selection.
The essay turns MCP adoption into a decision ladder: static files, APIs, CLI tools, and narrower contracts first.
The essay separates learned style, retrieved facts, and prompt behavior so each concern carries a smaller boundary.
The essay closes the graph around existing Ladder pieces by mapping task framing, current facts, repeated behavior, external action, prevention, and proof to their proper system surfaces.
The graph article explains why explicit nodes, edges, budgets, and gates make agent loops inspectable before autonomy grows.
Links
The centerpiece comparison maps Anthropic TypeScript SDK, OpenAI Agents SDK, and LangGraph to three different agent jobs, with a matrix and selection tree.
The follow-up essay explains why the Trinity repos ship runnable examples, repo-local MCP stubs, file-backed graphs, and provider-binding seams so a reader can bring a model without losing the pattern.
The follow-up essay explains why the Trinity repos begin with file-backed graphs, repo-local MCP reads, and explicit upgrade triggers instead of starting with hosted graph gravity.
The follow-up essay explains why the Trinity repos expose shadow tribunal seams, why second opinions should begin as non-blocking sentinels, and how weekly comparisons turn disagreement into evidence.
The source corpus names the ladder, its proof needs, page integration pattern, and maintenance rules before public presentation.
Links
The ladder hub gives each AI system layer a rung, autonomy pattern, determinism purchase, failure mode, and receipt trail.
Each published article carries ladder metadata and a sidecar showing rung, trade, failure mode, and receipt links.
Every build note carries ladder placement, public influences, axiom outcomes, and receipt references for agent-readable evidence.
The ledger turns the planning inventory into a public surface with status, ladder role, evidence artifact, checks, links, and next-proof gaps.
The article and diagrams separate semantic graph meaning from hybrid persistence categories: relational, document, object, event, analytical, vector, search, cache, and ledger-style storage.
The MCP primer explains the protocol in plain language and links the public StoneyTECH endpoint boundary.
Links
Partial
The MCP reads the generated public contract and exposes published content only: pages, essays, axioms, builds, repository notes, applied evidence, ladder placements, and receipts.
The public build note frames GVAR as citation-first learning from Google DeepMind Aletheia and Gemini Deep Think work, with no originality claim.
Links
The private GVAR workflow patch proved a topology gain: self-verify mode bypasses generation and reuses the same verifier input shape.
The follow-up essay ties learning-agent, evidence-agent, and gvar-engine into one architectural claim: determinism moves into loop boundaries, evidence contracts, and explicit graphs as job shape changes.
The public MCP now exposes receipt lists and per-item receipt lookups while existing content tools retain ladder placement metadata.
Planned
A future StoneyTECH public repo should package the read-only MCP, release manifest, negative-data contract, and smoke test from clean history.
Links
A future repo should show a synthetic generate, verify, adjudicate, refine loop with citations to Aletheia and no private workflow leakage.
Links
A future repo should show deterministic graph state, replay fixtures, branch gates, and convergence receipts using synthetic examples.
Links
A future CLI or small app should generate a layer-by-layer threat table with public OWASP and MITRE citation fixtures.
Links
A future selector should map residency, security, latency, cost, and operating constraints before model or provider choice.
Links
A future package or recipe should publish the glossary data shape, sidecar component pattern, accessibility rules, and public export checks.
Links
A future ops receipt should cover D1 write reliability, compaction or rotation, and reconcile persistence for work claims.
Links
Every merged public artifact updates the receipt inventory, adds a ladder role, links public evidence, names the current checks, and records the next proof gap.