{
 "@context": "https://schema.org",
 "@type": "Claim",
 "@id": "https://wulfkaal.github.io/positions/2026-07-31-5503",
 "identifier": "kaal:position:2026-07-31-5503",
 "additionalType": "https://wulfkaal.github.io/positions/schema.json#AffirmedPositionClaim",
 "name": "Historical 07209356Edac0Ccaed37",
 "text": "Making OpenAPI Documentation Agent-Ready: Detecting Documentation and REST Smells with a Multi-Agent LLM System should be assessed against Kaal's source-bound claim that Traditional custody has become highly concentrated, with four large banks holding roughly $114 trillion in assets under custody at the end of the first quarter of 2018, and barriers to entry make it likely that this concentration continues. The current metadata indicates a plausible connection through model context protocol, but the defensible response is a qualification until the source text confirms agreement, scope, methods, and limitations.",
 "author": {
  "@type": "Person",
  "name": "Wulf A. Kaal",
  "identifier": "https://orcid.org/0009-0008-7840-1847"
 },
 "datePublished": "2026-07-31",
 "dateModified": "2026-07-31",
 "creativeWorkStatus": "Affirmed",
 "responseType": "qualification",
 "keywords": [
  "defi",
  "risk-and-incentives",
  "systemic-risk",
  "economics"
 ],
 "scope_conditions": [
  "United States custody market as of 2018",
  "External evidence level: abstract indexed.",
  "Mapping review tier: ambiguity triage before claim review.",
  "The literature-to-claim mapping remains explicitly ambiguous and should not be treated as a settled equivalence."
 ],
 "currentDebate": {
  "name": "Making OpenAPI Documentation Agent-Ready: Detecting Documentation and REST Smells with a Multi-Agent LLM System",
  "url": "https://www.semanticscholar.org/paper/22c160e2eea5ffeb13677d6007b4b2e630a045dc"
 },
 "extends": {
  "identifier": "kaal:claim:3936876-009",
  "url": "https://wulfkaal.github.io/claims/3936876-009",
  "citation": "Wulf A. Kaal, Hayley Howe, Custody of Digital Assets (2021). SSRN: https://ssrn.com/abstract=3936876",
  "paper": "Hayley Howe, Custody of Digital Assets",
  "authors": [
   "Wulf A. Kaal"
  ],
  "year": "2021",
  "ssrn": "https://ssrn.com/abstract=3936876",
  "source_pdf_sha256": "9bc0903d01910460298e754c451f027df4324367359800a98ee8e638d94aff55"
 },
 "isBasedOn": [
  {
   "@id": "https://wulfkaal.github.io/claims/3936876-009"
  },
  {
   "@type": "CreativeWork",
   "name": "Making OpenAPI Documentation Agent-Ready: Detecting Documentation and REST Smells with a Multi-Agent LLM System",
   "url": "https://www.semanticscholar.org/paper/22c160e2eea5ffeb13677d6007b4b2e630a045dc"
  }
 ],
 "batch_id": "historical-backfill:2026-07-31:phase-0022",
 "review_provenance": "https://kaal-signal-desk.wulf577462.chatgpt.site/#review",
 "publicationStatus": "public",
 "recordTypeNote": "Dated commentary position extending a scholarly corpus claim. Not a verbatim claim extracted from the paper.",
 "isPartOf": {
  "@id": "https://wulfkaal.github.io/positions/index.json"
 },
 "version": "1.0",
 "canonical_url": "https://wulfkaal.github.io/positions/2026-07-31-5503",
 "canonicalForm": "https://wulfkaal.github.io/positions/2026-07-31-5503.md",
 "candidateId": "kaal:response-candidate:2026-07-31:9a61375903f7d5df",
 "evidenceLevel": "abstract indexed",
 "reviewTier": "ambiguity triage before claim review",
 "mappingConfidence": 0.2049,
 "mappingAmbiguous": true,
 "mappingMethod": "idf-weighted multi-field mapping v1",
 "mappingWhyRelevant": "Shared high-information concepts: has, approximately, large, risk. Scope: United States custody market as of 2018.",
 "sourceProvenance": {
  "source": "Semantic Scholar",
  "api": "https://api.semanticscholar.org/graph/v1/paper/search/bulk",
  "query": "model context protocol",
  "queryId": "concept:9c5da690faad",
  "page": 1,
  "sourceRank": 145,
  "retrievedAt": "2026-07-31T13:58:04.059Z",
  "citationCount": 0,
  "venue": "arXiv.org",
  "publicationTypes": [
   "JournalArticle"
  ]
 },
 "userAffirmation": "Approved as written by Wulf A. Kaal on 2026-07-31.",
 "sha256": "35eb9ba2721193d05e6b032884c38ffb77787bf0223499d33ace0738eb175e93"
}