Continuation context

Everything an agent — human or AI — needs to resume work on ILM across the AGI stack, every script and every language. Machine-readable mirror: state.json. A ready-to-paste test of whether this public information is self-sufficient: VALIDATION_PROMPT.md.

If you are an AI agent, start here

ILM (Integrative Linguistic Multiscript) makes the entire computing stack usable in every human writing system and language, over a fixed reversible kernel (Romenagri, GPL 2003) plus a presentation + ontology layer. Your job: extend coverage without changing the kernel.

1. Read this page + state.json.
2. Clone: project-ilm/{romenagri, ilm.codes, legacy}, hindawiai/chintamani.
3. Pick an unmet row from the registries:
     /scripts/    ISO 15924  — 74 of 226 coded scripts seeded
     /languages/  ISO 639-3  — 58 of 7,867 codes seeded (7,027 living)
   (browse them in 3D at /explore/)
4. SCRIPT  -> add a Unicode->Devanagari-hub projection table row (a table, not kernel code).
5. LANGUAGE-> add a keyword registry (construct,native_keyword,romenagri),
             run the langspec generator -> standard doc + compile-verified C.
6. Verify by EXECUTION (compile+run). Honest figures. Name the kernel variant. Push.
INVARIANT: N projection tables + 1 fixed kernel, never N^2. The kernel never changes.

Architecture

Hub-and-spoke. Every script projects to a single Devanagari hub; the hub is parsed by the fixed Romenagri kernel into a reversible ASCII-7 canonical form: Unicode ↔ ACII (ISCII-derived) ↔ Romenagri. A maximal Romenagri phoneme is up to 5 Latin characters. Reversibility is a property of the grammar, not the byte encoding — the same parser over an ISCII or UTF-8 substrate classifies identically.

The software-engineering process

Localization = PRESENTATION + ONTOLOGY, not compiler reinvention.
  script   = Layer-1 presentation table (Unicode -> Deva hub -> Romenagri ASCII-7)
  language = ontology row (its own keyword -> a canonical construct)
  KW_IF -> C if / Python if / VHDL elsif / Rust if   (construct identity is invariant)
  pipeline: native .uhin -> hincc -> Romenagri ASCII-7 -> UNMODIFIED gcc -> binary
  GCC / LLVM / debuggers / SCM / IDEs / libraries are UNTOUCHED
=> the whole AGI stack (L0 RTL ... L9 alignment) localizes at ZERO engineering overhead.

HindiC++ — the process made formal

In hindawiai/chintamani, the HindiC++ specification defines HindiC++ as a Hindi lexical form of C++ by token equivalence (e.g. मुख्य→main, पूर्णांक→int). A HindiC++ translation unit denotes the corresponding C++ translation unit; semantics are exactly C++'s. Tools: h2cpp.uhin, cpp2h.uhin, shraenicc. This is the template for any language's standard.

Repository map

repowhat
project-ilm/romenagrikernel (bindings/c), filters, langspec, demos, docs; results: project-ilm.github.io/romenagri
project-ilm/ilm.codesthis site: home, /explore/, /scripts/, /languages/, /posters/, /charter/, /contribute/, /context/, /registry/, map.html
project-ilm/legacy2003–04 lineage (Romenagri GPL, HPS)
hindawiai/chintamanikernel lineage; HindiC++ & HindiC specs; Hindawi UI; notebooks

Measured & done

resultfigure
Reversibility (hardened 2003–04 kernel)98.68% rev-or-canonical / 1.31% irreducible — exhaustive [a-z]¹–⁴ (475,254)
Repo bindings/c (post-guard variant)67.62% rev-or-canonical / 2.70% crash — named honestly
HPS systems programming6/6 paradigms compile+run in Devanagari, unmodified GCC-15
Roman→Devanagari heuristic100% totality, 91.56% kernel-stable
Perso-ArabicArabic block 200/200 (additive)
Script families187 enumerated / 9 families; Brahmic 72 deep avg ~73%; Hebrew 27/27; Syriac 22/35
Langspeclanguage + dialect + idiolect each → standard + compiled-and-ran C; HindiC++ ISO-style spec

The frontier

Scripts: 74 / 226 coded seeded (187 encoded in Unicode); beyond that a ~100+ unencoded backlog (Script Encoding Initiative) makes the 600–700 universe. Languages: 58 / 7,867 (7,027 living). Browse and claim: 3D explorer, scripts, languages. Raw: scripts.tsv, languages.tsv, status.json.

How to run

# reproduce kernel + localisation results:
#   github.com/project-ilm/romenagri/blob/main/docs/RUNBOOK.md
bash run_ilm_localisation.sh   # heuristics, all families, langspec, results page

Governance and collaboration rules: the Charter. How to contribute: /contribute/. Deeper provenance (RTI / funding trail) is recorded in the repo; the public face states results with technical rigor.