k-dense-byok vs paperjury
The two are close in size: 1.1k stars for k-dense-byok, 1.1k for paperjury. Over the days we have tracked them k-dense-byok moved +23.5% and paperjury +31%, so paperjury is growing faster right now.
They split the axes: k-dense-byok leads on privacy and model freedom and setup ease, paperjury on noise control.
Stars and commit dates come from our own daily tracking. The six axes are read off each project's documentation by our review pipeline, so they describe what a project says about itself, not what we measured in its code.
Where they stand today
A local-first, bring-your-own-keys AI research assistant that runs on your computer and bundles domain-specific scientific skills, workflows, and a living lab notebook.
- Stars
- 1.1k
- Tracked growth
- +23.5%
- Maturity
- ●●●●●
- Last commit
- 13h ago
- Language
- TypeScript
- License
- MIT
- Cost to run
- Your API key (pay-per-use) or free local models
Bundles a bounded, audit-ready review→decide→patch→recheck loop with ledgered issues and edit-safety safeguards, exposed as a Claude Code skill.
- Stars
- 1.1k
- Tracked growth
- +31%
- Maturity
- ●●●●●
- Last commit
- 22d ago
- Language
- JavaScript
- License
- MIT
- Cost to run
- Runs in your Claude session — model usage billed by the provider
Six axes, head to head
Each axis runs 0 to 5. The label under a score is what that project's own docs claim, not a category average.
| Axis | k-dense-byok | paperjury |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Whole-project access | ●●●●● Whole-repo analysis |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● Clarifying prompts & review | ●●●●● Severity gating & dedup |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Configurable skills & presets | ●●●●● Modes & personas |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Fully local optional | ●●●●● Cloud LLM via session |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● BYOK + local models | ●●●●● Claude-first (fixed) |
Setup ease What it takes to get a first useful run out of it. | ●●●●● Quick local start | ●●●●● Plugin install + session |
Which one to pick
Pick k-dense-byok if…
Privacy-first — run a full scientific assistant locally or use your own OpenRouter key while keeping projects and data on your machine, with many prebuilt scientific skills and workflows.
- Privacy: Fully local optional (5/5 against 3/5)
- Model freedom: BYOK + local models (5/5 against 3/5)
- Setup ease: Quick local start (5/5 against 3/5)
Pick paperjury if…
Audit-ready review loop — pick PaperJury when you want a pre-submission, multi-round reviewer simulation that produces minimal, author-confirmed LaTeX patches and deterministic compile/compliance checks.
- Noise control: Severity gating & dedup (5/5 against 3/5)
What people want from each one
K-Dense-AI/k-dense-byok
u7079256/paperjury
Questions people ask
Is k-dense-byok better than paperjury?
They split the axes: k-dense-byok leads on privacy and model freedom and setup ease, paperjury on noise control. k-dense-byok is worth picking when privacy-first — run a full scientific assistant locally or use your own OpenRouter key while keeping projects and data on your machine, with many prebuilt scientific skills and workflows.
Which of k-dense-byok and paperjury keeps my code private?
k-dense-byok: Fully local optional (5/5). paperjury: Cloud LLM via session (3/5).
What does each one cost to run?
k-dense-byok: Your API key (pay-per-use) or free local models. paperjury: Runs in your Claude session — model usage billed by the provider.
Full profiles: K-Dense-AI/k-dense-byok and u7079256/paperjury. Everything else in Research agents.