{"id":50451749,"url":"https://github.com/alvnukov/idt-lang","last_synced_at":"2026-06-01T00:30:47.825Z","repository":{"id":355419355,"uuid":"1227974437","full_name":"alvnukov/idt-lang","owner":"alvnukov","description":"Candidate executable language for formalizing physical structure and AI-assisted scientific reasoning","archived":false,"fork":false,"pushed_at":"2026-05-03T13:51:10.000Z","size":403,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-05-03T15:29:54.043Z","etag":null,"topics":["ai-research","executable-specification","formal-methods","scientific-computing","theoretical-physics"],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/alvnukov.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":"NOTICE","maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2026-05-03T12:26:29.000Z","updated_at":"2026-05-03T13:51:14.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/alvnukov/idt-lang","commit_stats":null,"previous_names":["alvnukov/idt-lang"],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/alvnukov/idt-lang","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alvnukov%2Fidt-lang","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alvnukov%2Fidt-lang/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alvnukov%2Fidt-lang/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alvnukov%2Fidt-lang/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/alvnukov","download_url":"https://codeload.github.com/alvnukov/idt-lang/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alvnukov%2Fidt-lang/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33755369,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-05-31T02:00:06.040Z","response_time":95,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai-research","executable-specification","formal-methods","scientific-computing","theoretical-physics"],"created_at":"2026-06-01T00:30:46.118Z","updated_at":"2026-06-01T00:30:47.812Z","avatar_url":"https://github.com/alvnukov.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# IDT Lang\n\n![QM Scientific Status](https://img.shields.io/badge/QM-context--first_Born--Hilbert_frontier-yellow)\n[![IDT v8 Lean CI](https://github.com/alvnukov/idt-lang/actions/workflows/v8-lean-status.yml/badge.svg?branch=main)](https://github.com/alvnukov/idt-lang/actions/workflows/v8-lean-status.yml)\n\nInherited Distinguishability Protolanguage (IDT) is a candidate executable\nlanguage for interpreting the physical structure of the universe, designed for\nboth human researchers and AI scientific agents.\n\nIts goal is not to replace physics by assertion. The goal is to provide a\ndisciplined map from observations to readouts, from hypotheses to bounded\nbridges, and from assumptions to explicit anchors and gates. If matured, IDT\ncould become a shared world-interpretation layer: a way for humans and AI\nsystems to organize evidence, test explanations, expose gaps, and progressively\ndeepen structural understanding of the physical world.\n\nThe project has a personal origin in a long-running attempt to make physical\nsystems intelligible, not only calculable. See [Origin and Motivation](ORIGIN.md)\nfor the human context behind the protolanguage.\n\n## Current Status\n\nThis repository is a clean public snapshot of the modular canonical source.\n\nThe current object is a reconstruction framework, not a completed replacement\nfor QM or GR. Its present value is methodological and test-directed:\n\n- explicit claim boundaries;\n- no-refit gates;\n- calibrated anchor protocols;\n- real-data fixtures;\n- a finite verifier that turns candidate bridges into auditable checks;\n- a role taxonomy for separating structural selectors, dimensional anchors,\n  couplings, bridge assumptions, readouts, experimental gates, and blocked\n  claims;\n- a research-graph contract for tracking which parts of the language are\n  implemented, partial, or still missing.\n\nFor a compact public boundary, see the [Public Claim Sheet](PUBLIC_CLAIM_SHEET.md).\n\n## AI Agent Quickstart\n\nAI agents should start from [AI Agent Guide](AI_AGENT_GUIDE.md), not from a full\nrepository scan.\n\nThe intended first context object is the compact v8 AI theory graph:\n\n```bash\npython scripts/build_ai_theory_graph.py --output dist/idt-v8-ai-theory-graph.json\npython scripts/query_ai_theory_graph.py --graph dist/idt-v8-ai-theory-graph.json validate --repo-root . --check-source-hashes\npython scripts/query_ai_theory_graph.py --graph dist/idt-v8-ai-theory-graph.json summary\n```\n\nThe graph is not committed to the repository and is not zipped. On a published\nGitHub Release, CI builds, validates, and attaches the raw JSON file\n`idt-v8-ai-theory-graph.json` as a release asset.\n\nUse this boundary when answering questions about the theory:\n\n- official project name: **IDT, Inherited Distinguishability Theory**;\n- current language/proof architecture: **Lean + IDT v8**;\n- proof authority: **Lean artifacts only**;\n- graph role: compact context/index for AI agents, not proof authority;\n- manifest role: residual research input, not proof truth;\n- current scientific status: reconstruction framework with finite gates,\n  conditional Lean routes, and explicit open frontiers; not a completed\n  derivation of QM or GR.\n\n## What This Snapshot Demonstrates\n\nThe current public value is that IDT turns speculative theory work into a\nchecked claim ledger. It shows which parts are finite executable readouts, which\nparts are calibrated, which bridges are still conditional, and which claims are\nblocked.\n\nCurrent auditable results:\n\n- finite QM readout gates: Born/context tables, two-path interference, Sorkin\n  `I3 = 0`, marker/eraser visibility, unitary context maps, projective readout\n  repeatability, Bell/CHSH no-signalling checks, amplitude-derived CHSH tables,\n  and a singlet angle model with `|S| = 2*sqrt(2)`;\n- anti-overclaim gates: the verifier rejects premature first-principles claims\n  for `hbar_I`, `G_I`, `alpha_em_I`, and `full_QM_I`;\n- calibrated-anchor discipline: `calibrated_hbar_I` may be used as an explicit\n  our-universe action anchor, while first-principles `hbar_I` remains blocked;\n- calibrated action-scale reconstruction: one shared\n  `phase_action_conversion_I` anchor is checked across energy-frequency,\n  momentum-wavenumber, action-phase, spectral, and interference fixtures, with\n  per-experiment refits rejected;\n- real-data weak-gravity gates: the SPARC front anchors real DDO154 data,\n  rejects post-fit residual provenance, records near misses, and rejects\n  held-out transfer for the current frozen candidate;\n- sector role taxonomy: selectors, dimensional anchors, couplings, bridge\n  assumptions, readouts, experimental gates, and blocked claims are separated\n  before public claims are allowed;\n- IDT-MetaLang research graph: claim roles and the dependency DAG are\n  implemented, while proof-status, prediction, failure-ledger, compact-core,\n  and theorem-card surfaces remain explicitly partial; its evidence references\n  are grounded against real manifest objects, schema surfaces, verifier checks,\n  or Markdown sections, and full-QM frontier blockers now have first-class\n  theorem cards.\n- v8 Lean-first migration: the language-level proof-status boundary,\n  context-first primitive base, and current stopped QM frontier are now encoded\n  in Lean under `Proofs/MetaLang/`. The old Python verifier is deprecated\n  compatibility infrastructure; the target proof architecture is Lean + IDT v8.\n  The first Lean-sourced experiment-protocol probe is available as\n  `lake exe idt_v8_protocol_status`; use `--json` for machine-readable status\n  `--documents-json` for the accepted IDT v8 document inventory,\n  `--residuals-json` for the Lean-sourced QM residual experiment list, and\n  `--check-boundary` for the current Lean boundary check. It reports the\n  certified-executable-check boundary and does not assign physical/QM\n  `formal_proof` status.\n- primitive-core contract: the current primitive surface is context-first.\n  Admissible context covers, local outcome-event presheaves, inheritance\n  transition families, facticization witnesses, and stable distinguishability\n  are the active lower-base candidates. The old history/event/readout scaffold\n  is now legacy compatibility only, not the current primitive base.\n- v7 context-first primitive-base boundary: the B1 Lean route constructor-binds\n  admissibility and no-target-import boundaries for the successor-base\n  candidate. The latest Born/Hilbert pass narrows the live readout frontier to\n  deriving context-first universal endpoint data from B0 or the accepted\n  successor base, while carrier-frontier exhaustion remains the Hilbert-side\n  universal quantifier.\n- v7 recovery layer: the full v7 research map is now preserved as Lean status\n  ledgers under `Proofs/QMClosure/V7*.lean`. The migrated surface covers\n  B0/projection boundaries, B1/B2 pressure, hypothesis batches, NUSD/FPD,\n  zero-base/search results, normalized-overlap/compressed finite-QM routes,\n  Born/readout, Schrodinger-frequency dynamics, Hilbert-carrier pressure, late\n  CGSC routing, and the full-QM burden ledger. This keeps prior research from\n  being collapsed into the v8 residual ledger; every recovered route remains an\n  obligation, conditional hit, rejected route, or wall rather than an upgraded\n  physical/QM proof.\n- QM semantic-kernel route: the current full-QM proof surface is grouped into\n  six conditional clusters covering 21 obligations: residual/projective,\n  representation, readout, dynamics, composite, and physical scale. B1 now\n  projects to this six-cluster kernel without losing package fields, and each\n  cluster has an explicit B1-projected theorem. This narrows the next proof\n  target to semantic content inside the open kernel core; it is not a proof of\n  `full_QM_I`.\n- QM semantic-content scaffolds: the finite projective, readout,\n  inheritance-action, product-tomography, monoidal associativity,\n  projective-limit, and calibrated-scale scaffolds are now compiled as a single\n  Lean bundle. This removes a proof-engineering gap for those finite fragments;\n  the later B1/CGSC artifacts fill the six structural target slots inside the\n  current package semantics.\n- CGSC structural target kernel: the six structural QM blockers are now\n  conditionally closed by one Lean artifact from seven context-generated stable\n  closure clauses, while preserving the no-target-import boundary. At this\n  layer alone the kernel is conditional; the next B1 derivation supplies the\n  clause source, while external QM adequacy remains open.\n- B1 CGSC clause derivation: all seven CGSC clauses are now machine-derived\n  from the B1 primitive-base witness interface in Lean, and the same artifact\n  fills the six structural target slots inside the current IDT package\n  semantics. The grounded CGSC layer now also exposes a claim-source aliasing\n  boundary: several named target slots currently share one smaller source\n  proposition, so these artifacts are source-witness scaffolds, not independent\n  physical derivations of local tomography, entanglement, spectrality, or exact\n  Born/Hilbert QM.\n  The remaining frontier is external adequacy: prove that this B1-derived\n  package reconstructs Hilbert/Born/unitary/tensor QM with the intended\n  universal physical meaning, not only as an internal obligation bundle. The\n  semantic-kernel evaluator can route those source-witness slots through the\n  current package, but the live open core must still separate slot filling from\n  target-specific derivation. The remaining\n  frontier is the all-context readout boundary: context-first universal endpoint\n  data. A new Lean bridge proves that the existing context-first constructive\n  witness package supplies primitive pairwise endpoint coverage, endpoint-stable\n  binary oriented contexts, and ternary-facticization blocking, so it selects\n  the Born-square readout without importing Born. The current primitive\n  discipline still admits a local ternary witness, and a B1-only endpoint-data\n  negative control is now checked, so current B1/scaffold closure does not\n  select universal Born by itself. The calibrated phase-scale bridge remains an\n  accepted boundary only, not a first-principles derivation of `hbar_I`; the\n  new action-scale reconstruction gate only tests one shared calibrated anchor.\n- Universal Born/Hilbert frontier: a new Lean contract closes exact universal\n  Born readout and frontier-scoped Hilbert representation together under\n  context-first universal endpoint data and carrier-frontier exhaustion. This is\n  a conditional frontier\n  closure, not a B0-alone derivation and not a proof of `full_QM_I`; the live\n  lower obligations are deriving that context-first endpoint data from B0 or the\n  accepted successor base and proving carrier-frontier exhaustion without\n  importing Born or complex Hilbert space.\n- Proper subcontext endpoint exhaustion front: the current broad QM pass is\n  recorded as a research ledger. The finite 35-experiment telemetry is passing\n  as executable evidence, while the exact frontier remains a candidate lower\n  principle: endpoint-stable proper-subcontext witnesses must exhaust stable\n  readout invariants and block primitive whole-context ternary residue. A new\n  Lean bridge shows that CFS-ready pairwise actualization conditionally closes\n  exact universal Born readout. A smaller Born-only core now separates the\n  readout wall from the Hilbert/carrier wall; it is still not a B0 derivation or\n  a proof upgrade.\n- QM research task ledger: the next-step plan is now encoded in Lean as\n  `Proofs/MetaLang/V8QmResearchTaskLedger.lean`. It records active blockers\n  for claim-source alias splitting, product/local-tomography targets,\n  Born-core derivation, carrier-frontier exhaustion, and experiment recompiles.\n  The ledger is a planning artifact and explicitly preserves the current\n  Born/Hilbert blockers.\n- facticizable distinguishability closure frontier: the candidate lower-level\n  principle says that stable inherited distinguishability must have finite\n  admissible readout witnesses; hidden joint invariants, global fact tables,\n  unconstrained GPT cones, and nonfinite residuals are tracked as negative\n  controls without closing QM.\n- QM frontier probe: the verifier audits the route to `full_QM_I` as diagnostic\n  cells. Earlier hard blockers have been narrowed into explicit proof\n  frontiers: context-first universal endpoint data, carrier-frontier exhaustion,\n  and first-principles action scale.\n- fundamental-unknownness bridge audit: the current base-theory search compares\n  the QM proof frontier with gravity/clock/source routes. It records six\n  candidate bridge principles and four route candidates, including possible\n  Hilbert and Bell routes, while preserving the status that Hilbert, Bell\n  derivation, and shared action scale are not closed.\n- Hilbert/spacetime bridge audit: the possible Hilbert/Bell/gravity connection\n  is now tracked with an explicit GR-reflection boundary. Metric/GR structure\n  may only enter as a readout or limit candidate of deeper clock-source-context\n  structure, not as a primitive foundation.\n- Hilbert/Bell/gravity scale probe: the broader candidate link is tracked as a\n  scale-hidden common-source route. QM-scale gates may expose Hilbert/Bell\n  readouts while gravity-facing clock/source response remains suppressed or\n  unresolved; this is recorded as an open research route, not a proof.\n- proof-verification ledger: current `formal_proof` markers are finite\n  IDT-Core/meta-invariants only, and they must be covered by proof cards with\n  machine-checkable artifacts and commands. The current proof pipeline first\n  synchronizes the generated Lean finite-core semantic artifact against the\n  manifest, then runs Lean 4 plus the IDT verifier.\n\nThese are successes of reconstruction discipline and executable claim control.\nThey are not claims that IDT has already derived all of QM, GR, or the constants\nof nature.\n\n## Repository Layout\n\n- `AI_AGENT_GUIDE.md` — compact entry point for AI agents: graph workflow,\n  primitives, status boundaries, and perspective.\n- `ORIGIN.md` — project origin and motivation.\n- `PUBLIC_CLAIM_SHEET.md` — public claim boundary and current auditable\n  successes.\n- `PROTOLANGUAGE.md` — canonical entry point and public positioning.\n- `sections/` — modular theory body.\n- `scripts/graph_query.py` — file-based research graph query and cautious edit\n  helper for the verifier manifest.\n- `scripts/build_ai_theory_graph.py` — compact source-grounded theory graph\n  packer for AI agents.\n- `scripts/query_ai_theory_graph.py` — read-only v8 graph query CLI for\n  summaries, local neighborhoods, references, and source pointers.\n- `theory_verifier/ai_theory_graph.py` — shared typed graph library used by the\n  packer and query CLI.\n- `scripts/sync_formal_proof_ledger.py` — generates/checks the Lean finite-core\n  semantic proof artifact from the current manifest.\n- `scripts/check_proofs.py` — runs proof-card checker commands.\n- `scripts/check_declarative_rules.py` — checks v8 declarative rule files.\n- `scripts/check_all.py` — one-command local verifier, proof, and test pipeline.\n- `Proofs/` — Lean proof artifacts.\n- `Experiments/` — Lean-sourced executable protocol probes.\n- `rules/v8/` — declarative v8 verification specifications.\n- `theory_verifier/` — compatibility Python package; `declarative.py` remains\n  the active IDT v8 input checker, while the legacy manifest verifier is not\n  proof authority.\n- `theory_verifier_manifest.json` — current machine-checkable manifest.\n- `tests/` — verifier unit tests.\n- `data/` — documented data anchors used by verifier-facing research notes.\n\n## Language Policy\n\nEnglish is the canonical language of the project. The primary README, canonical\nsource, verifier manifests, code, tests, and release notes should remain in\nEnglish.\n\nTranslations into other languages are welcome as secondary documentation, but\nthey must preserve the same claim boundaries as the English source. If a\ntranslation conflicts with the English canonical text, the English text is\nauthoritative.\n\n## License\n\nThis repository is licensed under the Apache License, Version 2.0. See\n[`LICENSE`](LICENSE) and [`NOTICE`](NOTICE).\n\n## Verify\n\nFetch external SPARC data first:\n\n```bash\npython3 scripts/fetch_sparc_data.py\n```\n\nThen run:\n\n```bash\npython3 scripts/check_all.py\n```\n\nThe proof-only lane is:\n\n```bash\npython3 scripts/check_proofs.py\n```\n\nThe IDT v8 Lean CI lane behind the `IDT v8 Lean CI` badge runs:\n\n```bash\nruff check theory_verifier tests scripts\nmypy --strict theory_verifier tests scripts\npython3 scripts/check_declarative_rules.py --json\npython3 -m unittest tests.test_declarative_verifier\nlake build Proofs\nlake build idt_v8_protocol_status\nlake exe idt_v8_protocol_status -- --check-boundary\nlake exe idt_v8_protocol_status -- --json\npython scripts/build_ai_theory_graph.py --output dist/idt-v8-ai-theory-graph.json\n```\n\nThis is the current Lean + IDT v8 migration-stop CI lane. It does not run the\nlegacy manifest verifier as proof authority and does not claim QM is proved.\n\n## AI Theory Graph\n\nThe v8 AI theory graph is a compact index for agents, not proof authority. Lean\nremains the proof source of truth, and the manifest is treated as residual\nresearch input.\n\nThe graph is not stored in git and is not zipped. On a published GitHub Release,\nCI attaches the raw JSON file `idt-v8-ai-theory-graph.json` as a release asset.\nTo generate the same file locally:\n\n```bash\npython scripts/build_ai_theory_graph.py --output dist/idt-v8-ai-theory-graph.json\n```\n\nFor changes to the accepted theory surface or the IDT research-language/tooling\nsurface, publish a semantic-versioned GitHub Release after committing. The\nrelease workflow is what produces the raw graph asset for that version. The tag\nmust follow the versioning rule in [PROTOLANGUAGE.md](PROTOLANGUAGE.md): use\n`MAJOR` for incompatible baseline/proof-boundary changes, `MINOR` for compatible\nnew theory/language/tooling surface, and `PATCH` only for corrections or\nhardening that preserve the accepted surface.\n\nAgents should load this compact graph first, inspect node/edge topology, then\nfetch exact source files by the recorded source path and hash only when more\ncontext is needed. The graph is context and navigation metadata; it does not\nupgrade claims and does not replace Lean artifacts.\n\nFor local graph inspection:\n\n```bash\npython scripts/query_ai_theory_graph.py summary\npython scripts/query_ai_theory_graph.py validate --repo-root . --check-source-hashes\npython scripts/query_ai_theory_graph.py show \u003cnode-id-or-alias\u003e\npython scripts/query_ai_theory_graph.py search \u003ctext\u003e --limit 20\npython scripts/query_ai_theory_graph.py neighbors \u003cnode-id-or-alias\u003e --depth 2\npython scripts/query_ai_theory_graph.py sources \u003cnode-id-or-alias\u003e --depth 1\n```\n\n## IDT Development MCP/RAG\n\nThe repository also provides a local stdio MCP server for source-grounded IDT\ndevelopment context:\n\n```bash\npython scripts/run_idt_mcp_server.py \\\n  --repo-root . \\\n  --graph dist/idt-v8-ai-theory-graph.json\n```\n\nThe server is read-only. Before each tool request it validates the configured\ngraph against source hashes and rebuilds it automatically if the graph is\nmissing or stale. The generated graph stays outside git; it is a live context\nindex for the local checkout, not a committed artifact. Graph refresh is guarded\nby an exclusive lock and atomic file replacement so concurrent MCP requests\ncannot read a partially written graph.\n\nIt exposes graph/RAG tools:\n\n```text\nidt_graph_summary\nidt_graph_search\nidt_graph_show\nidt_graph_neighbors\nidt_graph_sources\nidt_rag_retrieve\nidt_research_context\nidt_claim_audit\nidt_missing_proof_artifacts\nidt_graph_diff\nidt_lean_build_target\nidt_run_check\nidt_guarded_replace\n```\n\n`idt_rag_retrieve` uses the v8 graph plus exact source paths and hashes to\nreturn compact snippets. It is a development aid only: Lean remains proof\nauthority, the graph remains context/index metadata, and RAG output must not be\nused to upgrade claim status.\n\nFor safer research sessions, start with `idt_research_context` or\n`idt_claim_audit`. These tools are read-only: they summarize the local graph,\nsurface nearby dependencies and sources, and flag `formal_proof` residual claims\nthat are not grounded in Lean artifacts. They do not edit files, run proof\ncommands, or change claim status.\n\n`idt_graph_diff`, `idt_lean_build_target`, and `idt_run_check` provide a\ncontrolled execution layer. They return compact evidence packs rather than raw\nlogs, and their outputs are never proof authority by themselves. `idt_run_check`\nuses an allowlist (`graph_validate`, `declarative_rules`, `mcp_rag_tests`,\n`v8_protocol_boundary`) instead of arbitrary shell commands; `idt_lean_build_target`\naccepts only safe target names and runs `lake build \u003ctarget\u003e`.\n\n`idt_guarded_replace` is the only write-capable MCP tool. It performs a\nsingle-file text replacement only when the caller supplies the current `sha16`,\nthe old text occurs exactly once, the path is editable, and the replacement does\nnot introduce forbidden proof-status or overclaim tokens. It supports dry-run by\ndefault and writes under the same lock/atomic-replace discipline as graph\nrefresh. It intentionally refuses generated/internal paths such as `dist/` and\ndirect manifest edits.\n\n## Experiment Node Telemetry\n\nThe v8 experiment telemetry suite is a Lean-sourced executable research aid.\nLean defines the accepted protocol registry and logical nodes; the Python runner\nexecutes small deterministic fixtures and records which logical nodes were used,\nstressed, blocked, or failed.\n\nRun it locally with:\n\n```bash\nlake exe idt_v8_experiment_protocols -- --json\npython scripts/run_v8_experiment_suite.py \\\n  --output dist/v8-experiment-node-stats.json \\\n  --report dist/v8-experiment-report.md\n```\n\nThe JSON report uses schema `idt-v8-experiment-node-stats/1` and includes\nexperiment summaries, per-node statistics, telemetry rows, and source hashes.\nThe runner registers all 35 residual QM experiment IDs. The current mechanical\ncoverage implements deterministic telemetry fixtures for all 35 IDs across\nreadout normalization, calibrated action scale, Bell table compatibility,\ninterference, Sorkin `I3`, marker/eraser visibility, phase accumulation,\nspin-axis transitions, finite amplitude tables, projective repeatability,\ndecoherence/recoverability, Zeno samples, no-cloning/teleportation obstruction,\ncontextuality screens, weak readout, tunneling, HOM/antibunching, and finite\ngraph walk distributions. Use the report to see where finite fixtures place\npressure on logical nodes such as shared calibrated action scale, readout\nnormalization, interference visibility, phase accumulation, amplitude readout,\ncontextuality obstruction, and Bell table compatibility. This telemetry is\ncertified executable evidence only; it is not proof authority and cannot\nupgrade Born, Hilbert, Schrodinger dynamics, `hbar`, or full QM to proved\nstatus.\n\nThe older QM status lane is archived at `archive/legacy-ci/qm-status.yml`. It\nis retained as a compatibility/status recipe, not active proof-authority CI:\n\n```bash\nruff check theory_verifier tests scripts\nmypy --strict theory_verifier tests scripts\npython3 -m theory_verifier --json theory_verifier_manifest.json\npython3 scripts/check_declarative_rules.py --json\npython3 scripts/check_proofs.py\npython3 scripts/evaluate_born_direct_one_pass.py\npython3 scripts/evaluate_born_readout_attempt.py\npython3 scripts/evaluate_s2_born_proof_search.py\npython3 scripts/evaluate_qm_direct_one_pass.py\npython3 scripts/evaluate_cgsc_qm_one_pass_closure.py\npython3 scripts/check_qm_scientific_status.py\npython3 scripts/evaluate_qm_inevitability_route.py\npython3 scripts/evaluate_qm_hard_wall_probe.py\npython3 scripts/evaluate_qm_semantic_kernel_route.py\npython3 scripts/evaluate_qm_semantic_content_scaffolds.py\npython3 scripts/evaluate_born_wall_separation.py\npython3 scripts/check_born_scientific_status.py\npython3 scripts/evaluate_full_qm_proof_attempt.py\npython3 -m unittest discover -s tests\nlake build\n```\n\nThe `QM Scientific Status` badge reports the current scientific proof boundary:\nthe finite standard-QM sector is conditionally closed, and the active\nBorn/Hilbert frontier is context-first universal endpoint data plus\ncarrier-frontier exhaustion. The `IDT v8 Lean CI` badge reports whether the\nLean + IDT v8 migration-stop workflow is passing. Neither badge means that\nexact fundamental QM has been proved.\n\nThe underlying checks are:\n\n```bash\npython3 -m theory_verifier --json theory_verifier_manifest.json\npython3 scripts/sync_formal_proof_ledger.py --check\nlake env lean Proofs/IDTCore.lean\npython3 -m unittest discover -s tests\n```\n\nCompile the QM universal-pattern bench:\n\n```bash\npython3 scripts/qm_bench.py --json\n```\n\nOptional development tools:\n\n```bash\npython3 -m pip install -r requirements-dev.txt\nruff check .\nmypy --strict theory_verifier tests scripts\n```\n\n## Public Claim Boundary\n\nIDT may be described as a candidate executable language for physical\ninterpretation and AI-assisted scientific reasoning.\n\nIt must not be presented as:\n\n- a completed derivation of QM or GR;\n- a numerical derivation of \\(\\hbar\\), \\(G_N\\), or \\(\\alpha_{\\mathrm{em}}\\);\n- an explanation of dark matter or dark energy;\n- an experimentally confirmed replacement for established physics.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falvnukov%2Fidt-lang","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falvnukov%2Fidt-lang","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falvnukov%2Fidt-lang/lists"}