3.8 KiB
Cinnamonint Rainbow Raccoon Adapter Prior
Status: HOLD_EXTERNAL_PRIOR
Source: https://github.com/CinnamonInt/Cinnamonint/tree/master
Why It Matters
Cinnamonint is a deterministic sentence-reduction engine. It scans a sentence for registered token keywords, selects a token by priority and position, runs that token handler, replaces the handled part of the sentence, logs the iteration, and repeats until no tokens remain.
That gives the Research Stack a useful external prior for the Rainbow Raccoon Compiler because it has the same general shape:
input surface
-> token discovery
-> priority/route selection
-> local handler transform
-> iteration receipt
-> final reduced output
The important part is not the Python implementation. The useful idea is the receipt shape: one token, one local grammar, one bounded transform, one replay record.
Clean-Room Mapping
No Cinnamonint code is imported into the stack. The repository is GPL-3.0, and the stack should treat it as a reference prior unless an explicit compatibility decision is made later.
Mapping:
| Cinnamonint Surface | Research Stack Surface |
|---|---|
| Registered token | Finite logogram/operator entry |
| Token aliases | Grammar surface names |
| Token priority | Route-selection weight |
Handler handle(sentence) |
Local transformation primitive |
| One-token-per-call rule | Single-step bind transition |
| Iteration log | Replay receipt |
| Learn mode | Candidate operator synthesis |
| Token test suite | Promotion gate |
| Workshop mode | Mutable candidate registry |
| Hardened mode | Frozen receipt/replay registry |
| Subprocess isolation | Handler boundary / sandbox gate |
| Approval table | Human-reviewed execution gate |
Rainbow Raccoon Compiler Adapter
The adapter concept is:
sentence_or_logogram_stream
-> tokenize_against_finite_registry
-> select_next_operator(priority, position, route_cost)
-> apply_one_local_transform
-> emit_iteration_receipt
-> repeat_until_closed_or_nan0
RRC should keep this as a finite typed surface rather than open string matching:
TokenId : Fin n
AliasId : Fin m
Priority : Q0_16 or bounded UInt
StepReceipt := input_hash + token_id + handler_id + output_hash + residual
Promotion gate:
promote iff all token fixtures pass
and replay receipts close
and no destructive/imported handler runs without approval
and hardened registry hash is stable
NaN0 gate:
NaN0 iff unknown token required for progress
or iteration bound exceeded
or handler receipt missing
or output hash fails replay
or destructive/download/upload gate is unapproved
Fit With Existing Stack Work
Cinnamonint is a strong external prior for:
- whitespace-zero grammar: tokens can be counted instead of space-delimited once the grammar has explicit boundaries.
- logogram compilation: each logogram can behave like a token with a bounded handler and replay receipt.
- AMMR receipts: every reduction step can become a leaf; folded iteration segments become peaks.
- Rainbow Raccoon compiler triage: generated operators enter workshop mode, then only fixture-passing operators move to hardened mode.
- FPGA/prover cycle: deterministic token steps are small enough to lower into fixed-point or finite-state witnesses later.
Claim Boundary
This is an architecture prior, not an imported dependency and not a proof that Cinnamonint itself satisfies stack invariants. It supports a clean-room adapter: deterministic token reduction with bounded local transforms and replayable iteration receipts.
References:
- Cinnamonint README, GitHub, retrieved 2026-05-09.
- Cinnamonint design document, GitHub, retrieved 2026-05-09.
- Cinnamonint AGENTS.md, GitHub, retrieved 2026-05-09.
- Cinnamonint LICENSE, GPL-3.0, GitHub, retrieved 2026-05-09.