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PR-Agent

AI PR Review · #14 of 20 in category · #20 of 27 overall

Community-maintained, MIT-licensed PR reviewer with /review, /describe, and /improve commands, self-hosted with your own model keys.

[ Where it fits ]

On the documented evidence, PR-Agent suits teams that need the reviewer inside their own infrastructure, teams that want to read and fork the source, teams that want model choice and visible token costs.

[ Documented strengths ]

  • Economic Transparency. MIT-licensed BYOK via LiteLLM; pay providers at list price with full model choice, incl. local Ollama.

[ Documented gaps ]

  • Multi-dimensional Context. Per-PR review only; no codebase index or cross-repo context (per our open-source guide).
  • Continuous Learning. No learning from review history (per our open-source guide).
  • Sandbox Validation. Static per-PR analysis; no sandbox execution or test-run validation.
  • Measurable ROI. No dashboards or metrics (per our open-source guide).

[ Facts ]

Category
AI PR Review
Open source
Yes — MIT
Pricing
Free and open source (MIT); you pay only infrastructure and LLM API usage at provider list price. Transferred from Qodo to a community org in 2026 source ↗
Self-hosted
Yes — full stack — Runs as a CLI, Docker container, GitHub Action, or persistent webhook server on your own infrastructure.
Model control
Full BYOK via LiteLLM: OpenAI, Claude, Gemini, Mistral, DeepSeek, Azure OpenAI, Bedrock, Vertex, OpenRouter, local Ollama
Last verified
2026-08-11

[ Against the 9 standards ]

Based on public documentation as of 2026-08-11. ✓ documented · ~ partial · ✗ not offered · ? undocumented. Undocumented scores zero — see the methodology.

Multi-dimensional Context

Per-PR review only; no codebase index or cross-repo context (per our open-source guide).

~ Rule-Centric & Default Quiet

Configurable via TOML with your own conventions; no rule management UI or plain-language rules.

~ Dual-Workflow: Local vs. PR

Runs as CLI locally, in CI, or as PR commands; no distinct local-vs-PR behavior modes documented.

? Business Logic Validation

Ticket-compliance features not covered in the sources we verified.

Continuous Learning

No learning from review history (per our open-source guide).

Sandbox Validation

Static per-PR analysis; no sandbox execution or test-run validation.

Economic Transparency

MIT-licensed BYOK via LiteLLM; pay providers at list price with full model choice, incl. local Ollama.

~ Actionability

/improve generates code suggestions on the PR; apply flow varies by platform.

Measurable ROI

No dashboards or metrics (per our open-source guide).

[ PR-Agent vs the alternatives ]

[ Closest alternatives ]

[ In our coverage ]

[ FAQ ]

Is PR-Agent open source?

Yes. PR-Agent publishes its source under MIT, so you can read it, audit it and fork it.

Can PR-Agent be self-hosted?

Yes — full stack. Runs as a CLI, Docker container, GitHub Action, or persistent webhook server on your own infrastructure. Verified against the vendor's own documentation on 2026-08-11.

How much does PR-Agent cost?

Free and open source (MIT); you pay only infrastructure and LLM API usage at provider list price. Transferred from Qodo to a community org in 2026. Seat price is only part of the bill: PR-Agent handles models as full byok via litellm: openai, claude, gemini, mistral, deepseek, azure openai, bedrock, vertex, openrouter, local ollama, which is what usually decides the real monthly cost.

How does PR-Agent score against the 9-pillar AI code review standard?

2.5 out of 9. It fully documents 1 standard, partially documents 3, does not offer 4, and leaves 1 undocumented. The score is coverage of documented capability, not a measure of review quality.

What are the alternatives to PR-Agent?

The closest tools in this directory are Bito, Cursor BugBot, Gemini Code Assist, GitHub Copilot code review. Each is scored against the same 9 standards, so the matrices are directly comparable.

Evaluating PR-Agent?

Run it through the two-week trial protocol before you commit a team to it.

Evaluation guide [↗]