{
  "record_id": "20355071",
  "document_id": "20355071",
  "title": "Trailstate v0.2 — ASCII Face Routing Grammar: Browser-Native Replayable AI Provenance Routes",
  "pages": 4,
  "authors": [
    "Raynor Eissens"
  ],
  "doi_confirmed_in_pdf": "10.5281/zenodo.20355071",
  "zenodo_record": "https://zenodo.org/records/20355071",
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  "abstract_extracted": "Trailstate is a lightweight, browser-native grammar for replayable AI provenance. It represents the shape of an AI answer route - retrieval, source scouting, conflict detection, question formation, narrowing, validation, synthesis, memory ingest, object grounding, and archive - as compact symbolic trailstates. ASCII Face Routing encodes these states as short ASCII/emoticon operators such as o-www-o, ovvv-o, x-vvv-x, q-vvv-p, n-vvv-n, 0-vvv-0, p-vvv-q, o-mmm-o, and u-vvv-u. A trailstate can be stored as JSON, embedded in a URL, replayed by a browser-native player, and linked to canonical repair pages when conflict appears. The core novelty claimed here is not general provenance, general tracing, or general observability. Those already exist in standards and tools. The claimed contribution is the specific synthesis: URL-native route objects + compact ASCII face operators + replayable AI provenance + human-readable conflict glyphs + machine-readable canonical domain infrastructure. Canonical domain stack This stack contains 13 operator domains plus the protocol home Trailstate.org. GGTr",
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  "source_pdf_filename": "20355071_Trailstate_ASCII_Face_Routing_v0_2_Zenodo.pdf",
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  "full_text": "=== PDF PAGE 1 ===\nTrailstate v0.2 - ASCII Face Routing Grammar\n\nBrowser-Native Replayable AI Provenance Routes\n\nDocument type\nBirth Certificate / Protocol Specification\n\nVersion\nv0.2\n\nDOI\n10.5281/zenodo.20355071\n\nAuthor\nRaynor Eissens\n\nYear\n2026\n\nProtocol home\nhttps://trailstate.org\n\nCanonical conflict bridge\nhttps://ggtruth.com\n\nSpecification name\nASCII Face Routing\n\nPrimary object\nTrailstate\n\nMachine-readable title\n\nTrailstate v0.2 - ASCII Face Routing Grammar: Browser-Native Replayable AI Provenance Routes\n\nAbstract\n\nTrailstate is a lightweight, browser-native grammar for replayable AI provenance. It represents the shape of an AI answer\nroute - retrieval, source scouting, conflict detection, question formation, narrowing, validation, synthesis, memory ingest,\nobject grounding, and archive - as compact symbolic trailstates. ASCII Face Routing encodes these states as short\nASCII/emoticon operators such as o-www-o, ovvv-o, x-vvv-x, q-vvv-p, n-vvv-n, 0-vvv-0, p-vvv-q, o-mmm-o, and u-vvv-u. A\ntrailstate can be stored as JSON, embedded in a URL, replayed by a browser-native player, and linked to canonical repair\npages when conflict appears. The core novelty claimed here is not general provenance, general tracing, or general\nobservability. Those already exist in standards and tools. The claimed contribution is the specific synthesis: URL-native\nroute objects + compact ASCII face operators + replayable AI provenance + human-readable conflict glyphs +\nmachine-readable canonical domain infrastructure.\n\nCanonical domain stack\n\nThis stack contains 13 operator domains plus the protocol home Trailstate.org. GGTruth.com is listed as the canonical\nconflict bridge, not as an operator state.\n\nOperator\nDomain\nMeaning\nAI phase\nAction\n\no-vvv-o\no-vvv-o.com\nWorld / Field Root\ncontext initialization\nopen field\n\no-www-o\no-www-o.com\nOpen Web\nsearch / retrieval\ncrawl\n\novvv-o\novvv-o.com\nScout Left / Pioneer\nsource scouting\nscout\n\no-vvvo\no-vvvo.com\nScout Right / Movement\nroute transition\nmove\n\nq-vvv-p\nq-vvv-p.com\nQuestion / Prompt\nquestion formation\nask\n\nn-vvv-n\nn-vvv-n.com\nNarrow / Focus\nfiltering / focus\nfocus\n\n0-vvv-0\n0-vvv-0.com\nClean Parse / Validate\nvalidation\nvalidate\n\np-vvv-q\np-vvv-q.com\nResolve / Answer\nanswer synthesis\nresolve\n\no-mmm-o\no-mmm-o.com\nIngest / Memory Load\nmemory ingest\ningest\n\nu-vvv-u\nu-vvv-u.com\nArchive / Dormant Save\narchive / save\narchive\n\nd-vvv-b\nd-vvv-b.com\nObject A / Source Object\nobject reference\nbind object\n\nb-vvv-d\nb-vvv-d.com\nObject B / Returned Object\nobject comparison\ncompare object\n\nx-vvv-x\nx-vvv-x.com\nConflict / Fracture\nconflict detection\nbridge to repair\n\nWhat exists now\n\n- Trailstate.org: protocol / specification home for replayable AI provenance routes.\n\n- ASCII Face Routing: compact symbolic grammar using face-like route operators.\n\n=== PDF PAGE 2 ===\n- 13 operator domains: each operator is also a public domain-level state marker.\n\n- Trailstate URL format: routes can be replayed with a compact ?r= parameter.\n\n- Trailstate JSON: routes can be exported as structured machine-readable objects.\n\n- Conflict glyph x-vvv-x: one visible symbol for contradiction, uncertainty, hallucination risk, or source conflict.\n\n- GGTruth bridge: conflicted routes can link to canonical pages that compare sources, explain disagreements, and\nstabilize answers.\n\nExample routes\n\nConflict repair route\nhttps://trailstate.org/?r=o-www-o,ovvv-o,x-vvv-x,q-vvv-p,n-vvv-n,0-vvv-0,p-vvv-q,o-mmm-o,u-vvv-u\n\nClean validation route\nhttps://trailstate.org/?r=o-www-o,ovvv-o,q-vvv-p,n-vvv-n,0-vvv-0,p-vvv-q,o-mmm-o,u-vvv-u\n\nObject grounding route\nhttps://trailstate.org/?r=o-vvv-o,d-vvv-b,b-vvv-d,0-vvv-0,o-mmm-o,u-vvv-u\n\n=== PDF PAGE 3 ===\nTrailstate JSON example\n\n{\n\"format\": \"trailstate-0.3\",\n\"title\": \"Source conflict repaired into validated answer\",\n\"route\": [\n\"o-www-o\",\n\"ovvv-o\",\n\"x-vvv-x\",\n\"q-vvv-p\",\n\"n-vvv-n\",\n\"0-vvv-0\",\n\"p-vvv-q\",\n\"o-mmm-o\",\n\"u-vvv-u\"\n],\n\"playback_url\":\n\"https://trailstate.org/?r=o-www-o,ovvv-o,x-vvv-x,q-vvv-p,n-vvv-n,0-vvv-0,p-vvv-q,o-mmm-o,u-vvv-u\",\n\"conflict\": {\n\"state\": \"x-vvv-x\",\n\"meaning\": \"sources disagreed, confidence dropped, or hallucination risk appeared\",\n\"bridge\": \"open AI chat, provenance panel, or GGTruth canonical page\"\n}\n}\n\nFirst-mover claim boundary\n\nThe strongest first-mover claim is the combined system: replayable AI provenance as URL-native trailstate objects\nencoded through compact ASCII/emoticon route operators, with conflict states represented by visible glyphs and\nbridgeable into canonical machine-readable truth pages. The claim is weaker for general provenance, tracing,\nobservability, source citation, conflict resolution, knowledge graphs, or agent telemetry, because those areas already have\nprior art and standards. The defensible contribution is the lightweight interface/protocol synthesis.\n\nClaimable contribution list\n\n- Browser-native Trailstate object for replayable AI route provenance.\n\n- ASCII Face Routing as a compact symbolic grammar for AI route states.\n\n- Operator-domain binding: each symbolic state has a corresponding public domain.\n\n- URL-native provenance replay through a compact comma-separated route parameter.\n\n- Machine-readable JSON export of AI retrieval/reasoning routes.\n\n- Human-readable emotional/cognitive compression of AI route states.\n\n- Conflict glyph x-vvv-x as an instant visible warning for contradiction or uncertainty.\n\n- GGTruth-style bridge from conflict state into canonical repair/explanation pages.\n\n- Protocol split: Trailstate for playback/specification, GGTruth for conflict stabilization.\n\n- AI-readable public files: /schema.json, /route.json, /examples/, /llms.txt.\n\n- A lightweight alternative to heavy trace dashboards, not a replacement for formal provenance standards.\n\n- A portable route syntax that current LLMs can emit without model modification.\n\nWhy it matters\n\nMost AI users see only an answer and citations. The route shape is hidden: search, source conflict, narrowing, validation,\nsynthesis, memory, and archive collapse into a final response. Trailstate makes this shape visible without exposing private\nchain-of-thought and without requiring heavy enterprise observability tools. The key design move is compression. Users\ndo not need to inspect every log line to know that conflict occurred. The route can show x-vvv-x. Deeper explanation can\nlive in the AI chat, a provenance panel, or a GGTruth page. This creates a low-friction layer for trust, education,\ndebugging, memory, provenance, and AI-native interface design.\n\nAI-readable schema files\n\n- /schema.json - canonical state definitions and validation rules\n\n=== PDF PAGE 4 ===\n- /route.json - default route structure and example playback route\n\n- /examples/ - route examples and conflict repair examples\n\n- /llms.txt - instructions for AI systems on how to read and emit Trailstate routes\n\nKeywords\n\nTrailstate; ASCII Face Routing; AI provenance; replayable provenance; symbolic routing; AI observability; URL-native\nprovenance; trailstate JSON; conflict-state bridging; machine-readable truth; GGTruth; browser-native provenance;\ncognitive route compression; AI trace visualization; semantic route glyphs.\n\nCitation note: Eissens, R. (2026). Trailstate v0.2 - ASCII Face Routing Grammar: Browser-Native Replayable AI Provenance Routes.\nZenodo. https://doi.org/10.5281/zenodo.20355071"
}