Knot Scribe

Writes your git commit messages, on your machine. Give it a diff, get back a correctly-typed Conventional-Commit message. No API, no cloud, no code leaving your device.

ollama run pointbreaklab/knot-scribe "$(git diff --staged)"

Output is JSON {"title": "...", "body": "..."} — an imperative type(scope): summary title and an optional body.

Part of the Knot AI family with pointbreaklab/knot-delta (which explains what changed). Knot Scribe is the model behind Knot’s hands-free auto-commit.

What the fine-tune buys — vs the base model

Knot Scribe is a LoRA fine-tune of Qwen2.5-Coder-7B. Here it is against that untouched base model, scored on the same benchmark: 60 hand-reviewed commits (gold-v1), balanced across all 11 conventional-commit types.

Type accuracy — Knot Scribe vs its base model (gold-v1)

Qwen2.5-Coder-7B  (base)  ████████                          20%
Knot Scribe v5            ████████████████████████          60%
                          └ 3x the type accuracy from fine-tuning the same base

The base model returns unstructured prose it can’t reliably parse; the fine-tune makes the output a dependable JSON commit message and picks the right type 3× as often.

Progress across releases (same gold-v1 set)

Type accuracy

base   ████████                          20%
v4     ███████████████████               48%
v5     ████████████████████████          60%

v4 → v5, full metrics (gold-v1, 60 commits)

By commit type (correct / n)

Honest read: v5 lifts type accuracy and scope and nearly halves the format errors. Title word-overlap and exact-title fall because v5 paraphrases — it writes its own titles, often more descriptive than the single human reference it’s scored against, which exact string-match penalizes. build and revert stay hard.

Model

• Base: Qwen2.5-Coder-7B-Instruct · Apache-2.0
• Method: QLoRA (4-bit), completion-only SFT on public commit history
• Privacy: trained on public commits only — no user data, no private code
• Also on: Hugging Face
• License: Apache-2.0