NinFenz 宁封子 · NF

A content contract layer for AI long-form output

NinFenz (NF) turns "AI produces long-form content reliably" into engineering you can load, verify and reproduce. The protocol is domain-neutral and model-agnostic; narrative is only the first official domain pack.

Not a model · not a prompt-template collection · not a vendor SDK · MIT · runs offline

What it is / what it is not

It is: a protocol (module / pipeline / asset) plus one deterministic gate entry point plus a recomputable asset ledger - all plain markdown and JSON, stored in git.

It is not: a model, a prompt collection, or an SDK. The gates check structure and reproducibility, not prose quality - that boundary is part of the design.

Citable facts (every number has a source)

Run it in five minutes

# read-only checks, no clone needed
npx -y ninfenz doctor

# full-screen terminal TUI
npx -y ninfenz tui

# all 39 gates (needs a real checkout)
git clone https://github.com/Monyeah777/NinFenz
cd NinFenz && bash verify.sh

Requires Node >= 18.17 and Python >= 3.11 (standard library only, no pip dependencies).

See it running

Terminal TUI (standard library only, offline; 14-second demo):

NinFenz terminal TUI demo: deterministic gates and the asset view

How it differs from a prompt collection

Prompt collectionNinFenz
Deliverablea block of textprotocol + gates + asset ledger
Second runrandom structureisomorphic to the first (diffable against a baseline)
Pass/faila human eyeballs it39 deterministic checks against a frozen baseline
VerifiablenoMerkle inclusion proof + signature anchors, fail closed
Boundary-structure and reproducibility, not prose quality

Why the name

From the Liexian Zhuan: Ning Fengzi (宁封子) was the Yellow Emperor's Keeper of the Kiln - raw clay goes in; after kiln temperature and a seal, a durable artifact comes out. Kiln temperature maps to the deterministic gates; the seal maps to verifiable proof. NinFenz is the compressed form; NF is the short name.

FAQ

What is NinFenz?

A content contract layer: a protocol plus deterministic quality gates plus asset standards, so long-form AI output can be loaded, checked and reproduced.

Is it a model?

No. The protocol is model-agnostic; any model that can read text can assemble and load it.

How is it different from prompt templates?

Templates give text. NinFenz gives a protocol, verifiable gates and an asset ledger, so an output can be judged pass or fail.

Does it need network access?

No. The repo is markdown source; bash verify.sh reads locally and runs offline.

Can the output be verified?

Yes. Artifacts carry Merkle inclusion proofs (RFC 6962) and optional hmac / ssh-sig / sigstore anchors; a missing verifier fails closed instead of passing silently.

Licence and cost?

MIT, no paid tier, no hosted service.