GitGrit vs Pandorian
Last updated 2026-10-29.
The short answer: Both tools check your code against your engineering standards. Pandorian lets you write standards in plain English, and an LLM checks them on pull requests and repository scans. GitGrit runs standards as code, so most checks give the same answer every time, and uses an LLM only for rules that need judgment.
Who each one fits
Pandorian fits you if your standards already live in documents, you want to write new ones in plain English, and an LLM's judgment is a good fit for the rules you care about.
GitGrit fits you if you want checks you can rely on to give the same answer every time, a clear grade for every repository, and the option to read every line of the product or run it yourself.
At a glance
| Pandorian | GitGrit | |
|---|---|---|
| How a standard is written | Plain English or Markdown, or imported from your docs | Short, readable code (Python), or an LLM check when a rule needs judgment |
| Who decides pass or fail | An LLM | The code, for most standards; an LLM only where you choose |
| When it's checked | On pull requests, plus full-repository scans | On every push, pull request and tag, per branch |
| Scoping | Language, repository, service, team, path, initiative | Project, branch or tag pattern, event and language |
| Reporting | Organization-wide reports and dashboards | A grade from A+ to F per repository, with Required, Major and Minor standards |
| Open source | No | Yes (MIT), self-hostable, including air-gapped |
How they work
Pandorian
You write guidelines in plain English, or import them from documentation such as Confluence. An LLM reads each pull request and each repository and decides whether the code follows them. Standards can be scoped by language, repository, team, path and more, and results roll up into organization-wide reports. Pandorian has published research on writing guidelines an LLM can enforce, which reports that precision varies widely from one guideline to another.
GitGrit
In GitGrit, each standard is a short, readable piece of code that checks the repository directly, so the same code gives the same answer every time. When a rule truly needs judgment, such as "is the README clear enough for a new developer", a standard can use an LLM instead. Standards run in an isolated sandbox on every push, pull request and tag. Every repository gets a grade from A+ to F, and every failure shows exactly why.
FAQ
Why does "the same answer every time" matter?
When a check fails, your team needs to trust it. If the same code can pass one run and fail the next, people learn to ignore the result. Running standards as code keeps results stable, so a red result means something.
Can GitGrit check subjective standards too?
Yes. A GitGrit standard can use an LLM for rules that need judgment, using your own model provider. You choose where that makes sense.
Do I have to write code to use GitGrit?
No. Start with ready-made packs of standards in one click. Write your own when you need something specific.
Can I run GitGrit on my own infrastructure?
Yes. GitGrit is open source under the MIT license and can be self-hosted, including in air-gapped networks.
Talk to us
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