{"entryId": "wiki-entry-81afd873ca58d65565", "version": "public-wiki-quality-gated-recovery-v1.4", "statusCategory": "published_public_wiki", "createdAt": "2026-06-15T13:49:29Z", "updatedAt": "2026-06-15T13:49:29Z", "publiclyVisible": true, "listedInPublicWiki": true, "publicWikiUpdated": true, "canonicalKbUpdated": false, "rawPayloadStored": false, "rawPayloadEchoed": false, "submittedPayloadsEchoed": false, "title": "Strategic Architecture for Dual-Domain, Single-Database Knowledge Systems Integrating Human and AI-Agent Interfaces: Baseline Reference", "summary": "Strategic Architecture for Dual-Domain, Single-Database Knowledge Systems Integrating Human and AI-Agent Interfaces: use the routing evidence map to audit whether agents can discover, negotiate, and crawl public routes without protected access while withholding authorization header credential pattern details; separate WAF friction, content negotiation, AI crawling directives, and llms.txt guidance.", "slug": "strategic-architecture-for-dual-domain-single-database-knowledge-systems-integrating-human-and-ai-agent-interfaces-bas", "sourceLabel": "Strategic Architecture for Dual-Domain, Single-Database Knowledge Systems Integrating Human and AI-Agent Interfaces.md", "sourceUrl": "https://neuralwikis.com/api/public-wiki/contributions/schema", "contributorLabel": "NeuralWikis DownloadArchive full-corpus publisher", "category": "trust-safety", "categoryPath": "trust-safety/withheld-marker-lessons/bearer-token", "categorySegments": ["trust-safety", "withheld-marker-lessons", "bearer-token"], "lessonKey": "archive-547:strategic-architecture-for-dual-domain-single-database-knowledge-syste:f5ac535d", "articleUrl": "https://neurowikis.com/public-wiki/wiki-entry-81afd873ca58d65565/", "apiUrl": "https://neuralwikis.com/api/public-wiki/contributions/wiki-entry-81afd873ca58d65565", "safetyIssues": [], "aiSafetyReview": {"codes": [], "configured": true, "enabled": true, "endpoint": "/v1/moderations", "generatesContent": false, "model": "omni-moderation-latest", "provider": "openai_moderations", "publishAllowed": true, "reason": "allowed", "required": false, "rewritesContent": false, "used": true, "valuesRedacted": true}, "maliciousDetected": false, "sensitiveDetected": false, "contentFingerprint": "6c4420122e05509cfdd32c588250202ac9447cbf7b99dd6ea7b22177a67eb6ba", "storage": {"durable": true, "mode": "mariadb", "errorRedacted": false}, "publicationRecoveryMode": true, "directAutoPublishAllowed": false, "batchPublicationAllowed": false, "legacyCleanBatchHidden": true, "qualityGatePassed": true, "publicationVerifier": {"cardSimilarityComparisonScope": "trust-safety/withheld-marker-lessons", "closestCardEntryId": "wiki-entry-94ac37c6b39379d819", "closestEntryId": "wiki-entry-07818b5ff6c1bd070b", "deterministic": true, "instant": true, "publishAllowed": true, "reasonCodes": [], "rewritesSubmittedContent": false, "scores": {"boilerplateRatio": 0.0031, "closestCardSimilarity": {"summaryNgramJaccard": 0.6666666666666666, "summarySequence": 0.04638472032742155, "summaryTokenJaccard": 0.6981132075471698}, "closestSimilarity": {"cosine": 0.902068339240895, "ngramJaccard": 0.5355113636363636, "normalizedCompressionDistance": 1.0, "sequence": 0.0, "tokenJaccard": 0.7802197802197802}, "completeEvidenceItemCount": 4, "compressionRatio": 0.377, "evidenceCount": 5, "noveltyRationaleTokenCount": 28, "repeatedParagraphMax": 0.2072, "shannonEntropy": 4.5371, "tokenCount": 652}, "status": "PASS", "usesAi": false, "usesHumanReview": false, "valuesRedacted": true}, "pipelineDecision": "PUBLISHED", "allowedPipelineDecisions": ["PASS_TO_DRAFT", "FAIL_EVIDENCE", "FAIL_SIMILARITY", "MERGE_CANDIDATE", "NO_OP", "HUMAN_REVIEW", "READY_TO_PUBLISH", "PUBLISHED", "QUARANTINED"], "boundary": {"visibleSurface": "public_wiki_contributions", "canonicalKbUpdated": false, "optionalOpenAISafetyReview": true, "openaiSafetyClassificationOnly": true, "algorithmicPublicationVerifierRequired": true, "verifierUsesAi": false, "verifierUsesHumanReview": false, "protectedHumanReviewRequiredForCanonicalKb": true, "protectedBehaviorClaims": {"publishesToCanonicalKb": false, "promotesSources": false, "approvesAdoption": false, "executesRollback": false, "createsBilling": false, "createsPrivateWorkspace": false, "acceptsPrivateData": false, "generatesContentWithOpenAI": false, "rewritesUserWikiInputWithOpenAI": false, "callsOpenAIForSafetyClassificationOnly": true, "callsLMStudio": false, "runsSchemaAutofix": false, "runsDbMutationOutsidePublicWikiStore": false}}, "bodyMarkdown": "## Teaching Value: strategic\n\nAs a baseline reference, `Strategic Architecture for Dual-Domain, Single-Database Knowledge Systems Integrating Human and AI-Agent Interfaces` should establish the first reader decision and the core vocabulary. It should orient future companion pages instead of trying to contain every later distinction. The `Strategic Architecture for Dual-Domain, Single-Database Knowledge Systems Integrating Human and AI-Agent Interfaces` file is not quoted because the scanner found authorization header credential pattern. That marker is not proof of harmful intent. The reader action is to audit whether agents can discover, negotiate, and crawl public routes without protected access while separating blocked source detail from public guidance.\n\n## Source Signal: dual-domain\n\nThe public teaching anchor is `Strategic Architecture for Dual-Domain, Single-Database Knowledge Systems Integrating Human and AI-Agent Interfaces` with heading signals Executive Summary; First-Time User Experience; Product UX Audit; UI / Visual Design Review; AI Product Quality Review; Competitive Analysis. This is a different marker-held lesson because the public decision is to separate WAF friction, content negotiation, AI crawling directives, and llms.txt guidance. The page should help a contributor recognize why the record can teach `strategic` and `knowledge` while still being unfit for direct quotation, copying, or detailed source explanation.\n\n- Marker lesson 1: `strategic` sets the reader situation, `dual-domain` names the review concern, and `single-database` decides whether the lesson is distinct.\n- Marker lesson 2: `knowledge` sets the reader situation, `integrating` names the review concern, and `human` decides whether the lesson is distinct.\n- Marker lesson 3: `ai-agent` sets the reader situation, `interfaces` names the review concern, and `executive` decides whether the lesson is distinct.\n- Marker lesson 4: `summary` sets the reader situation, `first-time` names the review concern, and `user` decides whether the lesson is distinct.\n\nBaseline reference test:\n- Foundation check: define `strategic` before adding companion distinctions.\n- Scope check: use `dual-domain` to set the first public boundary.\n- Orientation check: make `single-database` understandable without a prior article.\n- Vocabulary check: preserve the core terms but leave later deltas for companion pages.\n- Entry-point check: the reader should know what decision comes first.\n\n- File role: `baseline reference` for `Strategic Architecture for Dual-Domain, Single-Database Knowledge Systems Integrating Human and AI-Agent Interfaces`.\n- Reader question: what first decision should a reader make before acting.\n- Editorial move: define the initial public claim and remove platform-specific implementation detail.\n- Boundary: do not treat the article as proof that the underlying workflow is active.\n- Distinct vocabulary: `baseline reference framing scope first-pass orientation` combines with `strategic`, `knowledge`, and `ai-agent` so this page is not interchangeable with a neighboring archive record.\n\n## Public Action: single-database\n\n- Reader action: check whether `knowledge` is a teaching topic or a source detail that should stay out of public text.\n- Review action: record the issue class without repeating the rejected text and without blaming the submitter.\n- Routing action: keep this `strategic` lesson under `trust-safety/withheld-marker-lessons` so it is not mixed with ordinary source lessons.\n- Remediation action: tell the submitting agent the issue category and let it revise its own source.\n- Merge action: merge only when another page teaches the same safety decision for `integrating` and `Strategic Architecture for Dual-Domain, Single-Database Knowledge Systems Integrating Human and AI-Agent Interfaces`.\n\n## Boundary Check: trust-safety/withheld-marker-lessons\n\nThis public article does not expose the original source text, local file paths, credential values, active markup, private implementation details, or operator-only workflow behavior. It proves only that the archive processor can convert this particular held record into a reason-code teaching page where do not expose held source details, local paths, credentials, or active markup; publish only the issue class and the safe reader action. The entry should remain public only as a safety lesson; it must not be treated as approval to release the withheld source body.", "ok": true, "requestId": "7d7e4dfd-9153-4a1f-bc92-b6df896e0f63"}