v5.0

Starnum Logic Engine
System Model Card

This document transparently describes the design principles, knowledge sources, applicable scope, and known limitations of the starnum.com.tw astrology analysis system. Last updated:

System Overview

ItemDescription
System NameStarnum Logic Engine v5.0
PurposeZi Wei Dou Shu and Numerology content generation and analysis assistance
Core SchoolLu Binzhao (Zhongzhou) Zi Wei Dou Shu + Pythagorean Numerology
Chart Engineiztro (open-source JavaScript, most actively maintained version on GitHub)
Knowledge Base366 files, 193,000+ lines of structured astrology text
Languages Supported10 languages (zh-TW, zh-CN, en, ja, ko, ms, th, id, vi, es)
Analysis Standards22 standard analysis blocks, 127 hard astrology rules auto-validated
Review MechanismMachine-readable quality gates, bounded AI verification, and human operator release authority
Document Versionv5.0, released 2026-04-12

Applicable Scope

This system is designed for

This system is NOT designed for

Important Disclaimer: All content generated by this system is for personal exploration and learning reference only. It does not constitute professional advice, nor is it a divination service. Life decisions ultimately remain yours to make. Astrology is a thinking tool, not a constraint on your destiny.

Knowledge Sources

The astrology knowledge base was built from cross-referencing 8 primary sources, totaling approximately 229 documents and 60,000+ lines of structured content. The Lu Binzhao (Zhongzhou) school serves as the unified standard.

Full source list and citation rules are in Research and AI Data Governance.

Known Limitations

Version History

v5.0
2026-04-12 — 127 hard astrology rules, knowledge base 366 files / 193K lines, case library 435 cases, zh-TW 1,772 articles
v4.3
2026-04-11 — Knowledge graph reference system, case backflow mechanism, 200+ bug fixes, glossary with 221 terms
v4.0
2026-04-07 — Fully automated pipeline, SHA256 content hash, cannibalization detection, GSC/Bing index tracking
v1.0
2026-03-27 — Initial launch, 232-item quality checklist

Related Resources

External standards and primary sources

These primary sources inform this page. They are benchmarks, not third-party endorsements of this site.

Current Machine Audit Snapshot

This block uses only traceable local audit data. No unsupported metrics or model claims are added.

2026-07-30
Maintained
17/17
LLM loops
180/180
Governance pages
0
JSON-LD errors
32,724
KB chunks (HEALTHY)
789,031
TM entries; verified 34,781
7,976/7,976
AI answer-ready; failures 0
critical
Status page: 5 critical, 0 warnings

Verifiable Evidence Layer

This block is not a narrative claim. Each core assertion has a claim id, source JSON, hash, and a repeatable verification command. Public pages disclose governance evidence without exposing source code, secrets, private data, or exploitable attack details.

Claim IDVerifiable valueStatusOwnerSource and verification
claim.public-url-manifest.indexable-count
Public URL and canonical inventory
38,965 indexable URLs verified sitewide node scripts/generate-public-evidence-manifest.js --dry
claim.trust-pages.audit-pass-rate
Trust page machine audit
180/180 pass verified sitewide node scripts/verify-trust-pages.js --check
claim.discovery-surface.zero-errors
AI discovery surface audit
{"errors":0,"warnings":0} verified sitewide node scripts/verify-discovery-surface.js
claim.structured-data.jsonld-errors
JSON-LD / structured data audit
{"structured_data_invalid_files":0,"breadcrumb_count":28274,"faq_count":27506,"dataset_count":30,"article_count":27406} verified sitewide node scripts/site-machine-audit.js
claim.status.sla-state
Status page SLA source
critical / 5 critical, 0 warnings verified sitewide node scripts/generate-status-page.js
claim.provider-alignment.openai-anthropic-gemini
OpenAI / Anthropic / Google Gemini benchmark alignment
benchmark alignment only unless code/config evidence exists verified sitewide node scripts/verify-public-evidence.js --check
claim.transparency-report.sha256
Transparency report SHA-256 anchor
{"report":"transparency/report-2026-Q3.json","sha256":"47b09e2ca4e8b8fe9dffdfaccef3b11212de9ee3a8a14badca8044e2481203c5"} verified sitewide node scripts/update-transparency-current-data.js
claim.release-integrity.gpg-signing
GPG signing status
GPG signing configured locally; GitHub verification pending github_verification_pending sitewide gpg --list-secret-keys --keyid-format=long && git log -1 --show-signature
claim.model-card.current-version
Model card version and stale check
{"current_version":"4.0.2","staleness_check":{"last_checked":"2026-04-16T14:25:40.228Z","is_stale":false,"stale_since":null}} verified model-card node scripts/verify-public-evidence.js --check
claim.model-card.skill-pack-inventory
Skill-pack and SOP version inventory
{"components":{"skill_packs":{"annual-content":"2026-04-11","article-translation":"2026-04-11","astrology-logic-validation":"2026-04-12","chart-analysis":"2026-04-13","content-fina verified model-card node scripts/verify-public-evidence.js --check
claim.model-card.answer-readiness
AI answer readiness audit
{"articles":7976,"aiAnswerReady":7976,"riskBoundaryArticles":2239,"failures":0} verified model-card node scripts/verify-public-evidence.js --check

System Card V2.0: Technical Transparency Layer

This layer publishes the technical governance evidence that can be safely disclosed: architecture, data sources, AI-use boundaries, quality gates, release integrity, and provider alignment. Source code, secrets, exploitable attack details, and private data remain out of scope.

Public architecture

Cloudflare Pages/Workers, R2/D1/KV/Pagefind, and local generation scripts form the public-site and governance publication chain. Public pages disclose behavior, state, and traceable sources, not secrets or internal permissions.

AI-use disclosure

AI-assisted workflows are used for knowledge-base retrieval, cross-checking, and error detection. Governance documents are benchmarked against OpenAI, Anthropic, and Google Gemini public frameworks. Production model usage is disclosed only when code/config evidence exists.

Quality and safety gates

Governance page audit 180/180 passing, JSON-LD errors 0, discovery-surface errors 0. Status pages report critical / 5 critical, 0 warnings as-is.

Data traceability

Knowledge base 32,724 chunks, TM 789,031 entries, AI answer-ready 7,976/7,976. Public metrics trace to data/state-machine/*, data/*audit*.json, and transparency reports.

Governance areaOpenAIAnthropicGoogle GeminiStarnum implementation evidence
Model/system-card disclosureOpenAI models + safety docsClaude model docs + system/model cardsGemini model docs + safety settingssystem-card, model-card, methodology, benchmark, transparency-log
Safety evaluation and use boundariesSafety best practices / deployment checklistResponsible Scaling / safety policyGemini safety controls / policyAI safety, acceptable-use, ethics, risk-boundary copy, crawler policy audit
Data governanceData controls / privacy controlsprivacy and data handling docsGemini API data governance referencesprivacy, ai-data-governance, KB/TM source tracking, SHA-256 hashes
Monitoring and releaseproduction checklist / eval disciplinesystem-card transparency disciplinemodel/version documentation disciplinedeploy.js, status.html, SLA report, trust-pages-machine-audit, sitemap/hreflang audits

The V2.0 goal is not more claims; it separates implemented controls from planned controls. Production usage, benchmark alignment, status exceptions, GPG signing, and SLA breaches are disclosed from source data.

Release Integrity And GPG

GPG signing configured locally. signingkey=0934DFA0EDA6363A. GitHub verification pending until the public key upload and Verified badge are confirmed.

OpenAI / Anthropic / Google Gemini Alignment

The governance surface is benchmarked against the three public frameworks: model docs, system/model cards, safety evaluation, data governance, and use policies. This is benchmark alignment, not a claim that every provider is active in production inference. Official docs checked: 2026-07-30

ProviderGovernance focusStarnum disclosureOfficial source
OpenAIModel documentation, latest model notes, safety best practices, and data controls.No verifiable production model setting was found in the production code scan; providers are listed as governance benchmarks.https://platform.openai.com/docs/models
AnthropicClaude model documentation, system/model cards, Responsible Scaling, and safety policy.No verifiable production model setting was found in the production code scan; providers are listed as governance benchmarks.https://docs.anthropic.com/en/docs/about-claude/models
Google GeminiGemini API model documentation, safety settings, data governance, and platform policy.No verifiable production model setting was found in the production code scan; providers are listed as governance benchmarks.https://ai.google.dev/gemini-api/docs/models